# EXAMPLES

COMPONENT: dsp
EXAMPLENAME: FilterInputSignalUsing1by2SIMOSystemSimulinkExample
EXAMPLETITLE: Filter Input Signal Using 1-by-2 SIMO System
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Filter an input signal using a 1-by-2 SIMO system with two distinct paths between the input and each output. Partition the filters to reduce latency.


COMPONENT: dsp
EXAMPLENAME: SplitMultichannelSignalsIntoSeveralMultichannelSignalsExample
EXAMPLETITLE: Split Multichannel Signals into Several Multichannel Signals
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Multichannel signals, represented by matrices in the Simulink environment, are frequently used in signal processing models for efficiency and compactness. Though most of the signal processing blocks can process multichannel signals, you may need to access just one channel or a particular range of samples in a multichannel signal. You can access individual channels of the multichannel signal by using the blocks in the Indexing library. This library includes the Selector, Submatrix, Variable Selector, Multiport Selector, and Submatrix blocks.


COMPONENT: dsp
EXAMPLENAME: ConfigureAndRunYourModelExample
EXAMPLETITLE: Configure and Run Your Model
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
In the previous topic, you configured your scalar quantization model for vector quantization by adding the LSF Vector Quantization subsystem. In this topic, you set your block parameters and quantize your reflection coefficients using the split vector quantization method.


COMPONENT: dsp
EXAMPLENAME: OverlapAddSaveExample
EXAMPLETITLE: Overlap-Add/Save
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Filter a sinusoid with the Overlap-Add and Overlap-Save FFT methods using the Frequency-Domain FIR filter block.


COMPONENT: dsp
EXAMPLENAME: TunableLowpassFilteringOfNoisyInputInSimulinkExample
EXAMPLETITLE: Tunable Lowpass Filtering of Noisy Input in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Filter a noisy chirp signal with a lowpass filter that has a tunable passband frequency. The filter in this example is designed using a Variable Bandwidth IIR Filter block with Filter type set to Lowpass . This type of filter enables you to change the passband frequency during simulation without having to redesign the whole filter. The filter algorithm recomputes the filter coefficients whenever the passband frequency changes.


COMPONENT: dsp
EXAMPLENAME: AnalysisAndSynthesisOfSpeechExample
EXAMPLETITLE: Analysis and Synthesis of Speech
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
A speech signal is usually represented in digital format, which is a sequence of binary bits. For storage and transmission applications, it is desirable to compress a signal by representing it with as few bits as possible, while maintaining its perceptual quality. Quantization is the process of representing a signal with a reduced level of precision. If you decrease the number of bits allocated for the quantization of your speech signal, the signal is distorted and the speech quality degrades.


COMPONENT: dsp
EXAMPLENAME: FilterNoisySignalUsingSOSFilterInSimulinkExample
EXAMPLETITLE: Filter Noisy Signal Using Second-Order Section (SOS) Bandpass Filter in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Filter a noisy sinusoidal signal using the Second-Order Section Filter block. Obtain the numerator and denominator coefficients of the SOS filter using the Bandpass IIR Filter Design block.


COMPONENT: dsp
EXAMPLENAME: IdentifyYourResidualSignalAndReflectionCoefficientsExample
EXAMPLETITLE: Identify Your Residual Signal and Reflection Coefficients
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
In the previous topic, Analysis and Synthesis of Speech, you learned the theory behind the LPC Analysis and Synthesis of Speech example model. In this topic, you define the residual signal and the reflection coefficients in your MATLAB® workspace as the variables E and K , respectively. Later, you use these values to create your scalar quantizers:


COMPONENT: dsp
EXAMPLENAME: RebufferSignalUsingDelayLineExample
EXAMPLETITLE: Rebuffer Signal Using Delay Line
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
In this example, the Delay Line block rebuffers a signal with frame size 4 to a frame size of 3 using the Delay Line block.


COMPONENT: dsp
EXAMPLENAME: GenerateSampleBasedSineWavesBlockExample
EXAMPLETITLE: Generate Sample-Based Sine Waves
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Compares the different methods of generating sample-based sine waves from the Sine Wave block in DSP System Toolbox.


COMPONENT: dsp
EXAMPLENAME: ReorderChannelsInMultichannelSignalsExample
EXAMPLETITLE: Reorder Channels in Multichannel Signals
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Multichannel signals, represented by matrices in Simulink are frequently used in signal processing models for efficiency and compactness. Though most of the signal processing blocks can process multichannel signals, you may need to access just one channel or a particular range of samples in a multichannel signal. You can access individual channels of the multichannel signal by using the blocks in the Indexing library. This library includes the Selector, Submatrix, Variable Selector, Multiport Selector, and Submatrix blocks. It is also possible to use the Permute Matrix block, in the Matrix operations library, to reorder the channels of a multichannel signal.


COMPONENT: dsp
EXAMPLENAME: HighResolutionFilterBankBasedPowerSpectrumEstimationExample
EXAMPLETITLE: High Resolution Filter-Bank-Based Power Spectrum Estimation
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Perform high resolution spectral analysis by using an efficient polyphase filter bank sometimes referred to as a channelizer.


COMPONENT: dsp
EXAMPLENAME: CodeGenerationForParametricAudioEqualizerExample
EXAMPLETITLE: Code Generation for Parametric Audio Equalizer
PRODUCT: MATLAB;DSP System Toolbox;Simulink;MATLAB Coder;Embedded Coder;Simulink Coder
DESCRIPTION:
Model an algorithm specification for a three band parametric equalizer which will be used for code generation.


COMPONENT: dsp
EXAMPLENAME: CountDownThroughRangeOfNumbersBlockExample
EXAMPLETITLE: Count Down Through Range of Numbers
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Use the Counter block to count down through a range of numbers. The Pulse Generator block drives the Dec port of the Counter block, and the N-Sample Enable block triggers the Rst port. All inputs to and outputs from the Counter block are multiplexed into a single To Workspace block using a 4-port Mux block.


COMPONENT: dsp
EXAMPLENAME: ModifyAdaptiveFilterParametersDuringModelSimulationExample
EXAMPLETITLE: Modify Adaptive Filter Parameters During Model Simulation
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
In the previous topic, LMS Filter Configuration for Adaptive Noise Cancellation, you created an adaptive filter and used it to remove the noise generated by the Acoustic Environment subsystem. In this topic, you modify the adaptive filter and adjust its parameters during simulation. This topic assumes that you are working on a Windows operating system.


COMPONENT: dsp
EXAMPLENAME: FilterNoisySignalUsingFOSFilterInSimulinkBandstopVersionExample
EXAMPLETITLE: Filter Noisy Signal Using Fourth-Order Section (FOS) Filter in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Filter a noisy sinusoidal signal using the Fourth-Order Section Filter block. Obtain the numerator and denominator coefficients of the FOS filter using the Bandstop IIR Filter Design block.


COMPONENT: dsp
EXAMPLENAME: ButterworthFilterExample
EXAMPLETITLE: Butterworth Filter
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Design an eighth order Butterworth lowpass filter with a cutoff frequency of 5 kHz, assuming a sample rate of 44.1 KHz.


COMPONENT: dsp
EXAMPLENAME: SolveMatrixEquationUsingCholeskySolverExample
EXAMPLETITLE: Solve Matrix Equation Using Cholesky Solver
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Use Cholesky Solver block to solve a matrix equation. Verify the solution using Matrix Multiply block.


COMPONENT: dsp
EXAMPLENAME: MultiphaseClockBlockExample
EXAMPLETITLE: Generate Five-Phase Output from the Multiphase Clock Block
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Use the Multiphase Clock block to generate a 100 Hz five-phase output in which the third signal is first to become active. The block uses a high active level with a duration of one interval.


COMPONENT: dsp
EXAMPLENAME: InheritSignalPropertiesViaOutputPortExample
EXAMPLETITLE: Inherit Signal Properties Via Output Port
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Select the Inherit via output port parameter to inherit the properties of the random signal through back propagation.


COMPONENT: dsp
EXAMPLENAME: LowpassFilterBlockExample
EXAMPLETITLE: Lowpass Filter Block
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
As an alternative to Filter Builder, you can use the Lowpass Filter block in your Simulink model. The Lowpass Filter block combines the design and implementation stages into one step. The filter designs its coefficients using the elliptical method, and allows minimum order and custom order designs.


COMPONENT: dsp
EXAMPLENAME: HighResolutionSpectralAnalysisInSimulinkExample
EXAMPLETITLE: High Resolution Spectral Analysis in Simulink
PRODUCT: MATLAB;DSP System Toolbox
DESCRIPTION:
Perform spectral estimation in Simulink using the filter bank method, and compare the performance with the Welch's averaged modified periodogram method.


COMPONENT: dsp
EXAMPLENAME: DesignADigitalFilterInSimulinkExample
EXAMPLETITLE: Design a Digital Filter in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
In this section, you use a Digital Filter Design block to create low frequency noise, which models the wind noise inside the cockpit.


COMPONENT: dsp
EXAMPLENAME: HighpassFilterSinusoidalSignalExample
EXAMPLETITLE: Highpass Filter Sinusoidal Signal
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Highpass filter a sinusoidal signal using the Highpass Filter block. Plot the spectrum of the original signal and the filtered signal in the spectrum analyzer.


COMPONENT: dsp
EXAMPLENAME: SortDataIntoAscendingAndDescendingOrdersExample
EXAMPLETITLE: Sort Data into Ascending and Descending Orders
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Use the Sort block to sort the input data into ascending and descending orders. The Array Plot shows the sorted and the unsorted data.


COMPONENT: dsp
EXAMPLENAME: Import3DArrayFromWorkspaceBlockExample
EXAMPLETITLE: Import 3-D Array From Workspace
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Import a 3-D array A from the MATLAB® workspace into the Simulink® model using the Signal From Workspace block. Use the To Workspace block to write the imported data to the MATLAB workspace. In this model, the To Workspace block slightly modifies data.


COMPONENT: dsp
EXAMPLENAME: ImportMatrixSignalsForSampleBasedProcessingExample
EXAMPLETITLE: Import Matrix Signals for Sample-Based Processing
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
The Signal From Workspace block generates a matrix signal that is convenient for sample-based processing. Beginning with the first page of the array, the block outputs a single page of the array to the output at each sample time. Therefore, if the Signal parameter specifies an M-by-N-by-P array, the output of the Signal From Workspace block is P M-by-N matrices representing M*N channels. The block receiving this signal does sample-based processing or frame-based processing on the signal based on the parameters set in the block dialog box.


COMPONENT: dsp
EXAMPLENAME: SplitMultichannelSignalsIntoIndivSigsExample
EXAMPLETITLE: Split Multichannel Signals into Individual Signals
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Multichannel signals, represented by matrices in the Simulink® environment, are frequently used in signal processing models for efficiency and compactness. Though most of the signal processing blocks can process multichannel signals, you may need to access just one channel or a particular range of samples in a multichannel signal. You can access individual channels of the multichannel signal by using the blocks in the Indexing library. This library includes the Selector, Submatrix, Variable Selector, Multiport Selector, and Submatrix blocks. It is also possible to use the Permute Matrix block, in the Matrix operations library, to reorder the channels of a frame-based signal.


COMPONENT: dsp
EXAMPLENAME: ViewTheCoefficientsOfYourAdaptiveFilterExample
EXAMPLETITLE: View the Coefficients of Your Adaptive Filter
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
The coefficients of an adaptive filter change with time in accordance with a chosen algorithm. Once the algorithm optimizes the filter's performance, these filter coefficients reach their steady-state values. You can view the variation of your coefficients, while the simulation is running, to see them settle to their steady-state values. Then, you can determine whether you can implement these values in your actual system:


COMPONENT: dsp
EXAMPLENAME: ComputeMovingStandardDeviationOfNoisyStepSignalExample
EXAMPLETITLE: Compute Moving Standard Deviation of Noisy Square Wave Signal
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Compare the sliding window standard deviation method and the exponentially weighted standard deviation method in Simulink using the Moving Standard Deviation block.


COMPONENT: dsp
EXAMPLENAME: InterpolateVariableSizeSinusoidalSignalExample
EXAMPLETITLE: Interpolate Variable-Size Sinusoidal Signal
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Interpolate a sinusoidal signal whose frame size varies during simulation. The Variable FIR Interpolation block determines the frame size of the interpolated output based on the value of the Specification parameter.


COMPONENT: dsp
EXAMPLENAME: BufferInputIntoFramesExample
EXAMPLETITLE: Buffer Input into Frames
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Multichannel signals of frame size 1 can be buffered into multichannel signals of frame size L using the Buffer block. L is greater than 1.


COMPONENT: dsp
EXAMPLENAME: DesignAndImplementIIRHalfbandDecimatorInSimulinkExample
EXAMPLETITLE: Design and Implement IIR Halfband Decimator in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Design and implement an IIR halfband decimator using the IIR Halfband Decimator block. Pass a noisy input through the decimator. Plot the spectrum of the input and the decimated subband outputs in the spectrum analyzer.


COMPONENT: dsp
EXAMPLENAME: DetectAnomaliesInSinusoidalSignalExample
EXAMPLETITLE: Detect Anomalies in Sinusoidal Signal
PRODUCT: MATLAB;Deep Learning Toolbox;DSP System Toolbox;Simulink
DESCRIPTION:
Use the Deep Signal Anomaly Detector block to detect anomalies in a sinusoidal signal. The block uses a detector that has been trained on a set of sinusoidal signals of constant frequency and amplitude. Use the time scope to plot the input, anomaly flag, and the window loss.


COMPONENT: dsp
EXAMPLENAME: DesignAndImplementIIRHalfbandInterpolatorInSimulinkExample
EXAMPLETITLE: Design and Implement IIR Halfband Interpolator in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Design and implement an IIR halfband interpolator using the IIR Halfband Interpolator block. Pass a noisy input through the interpolator. Plot the spectrum of the input and the interpolated output in the spectrum analyzer.


COMPONENT: dsp
EXAMPLENAME: ComputeTheHistogramOfRealAndComplexDataExample
EXAMPLETITLE: Compute the Histogram of Real and Complex Data
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Simulink model example that explains how the histogram bin boundaries are calculated based on the input.


COMPONENT: dsp
EXAMPLENAME: CreateSignalsUsingSignalFrmWorkspacBlockExample
EXAMPLETITLE: Create Signals Using Signal From Workspace Block
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
You can also use the Signal From Workspace block to create signals. In this section, the Signal From Workspace block creates a 2-by-2 signal with a sample period of 1 second.


COMPONENT: dsp
EXAMPLENAME: SplitMultichannelSignalsIntoIndividualSignalsExample
EXAMPLETITLE: Split Multichannel Signals into Individual Signals
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Multichannel signals, represented by matrices in the Simulink® environment, are frequently used in signal processing models for efficiency and compactness. Though most of the signal processing blocks can process multichannel signals, you may need to access just one channel or a particular range of samples in a multichannel signal. You can access individual channels of the multichannel signal by using the blocks in the Indexing library. This library includes the Selector, Submatrix, Variable Selector, Multiport Selector, and Submatrix blocks.


COMPONENT: dsp
EXAMPLENAME: FilterHighFrequencyNoiseInSimExample
EXAMPLETITLE: Filter High-Frequency Noise in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
In the previous topics, you used Digital Filter Design blocks to create FIR lowpass and highpass filters. In this topic, you use these blocks to build a model that removes high frequency noise from a signal. In this model, you use the highpass filter, which is excited using a uniform random signal, to create high-frequency noise. After you add this noise to a sine wave, you use the lowpass filter to filter out the high-frequency noise.


COMPONENT: dsp
EXAMPLENAME: DesignAndImplementLowpassFilterWithTunableFreqSpecsInSLExample
EXAMPLETITLE: Design and Implement Lowpass Filter with Tunable Frequency Specifications in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Vary the order and the cutoff frequency of the lowpass FIR filter during simulation. Design the filter every time the frequency specifications update. Visualize the magnitude response of this varying filter.


COMPONENT: dsp
EXAMPLENAME: EstimateTheTransferFunctionInSimulinkExample
EXAMPLETITLE: Estimate the Transfer Function in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
To estimate the transfer function of a system in Simulink®, use the Discrete Transfer Function Estimator block. The block implements the Welch's average modified periodogram method and uses the measured input and output data for estimation.


COMPONENT: dsp
EXAMPLENAME: AdaptiveNoiseCancellationUsingRLSAdaptiveFilteringExample
EXAMPLETITLE: Adaptive Noise Cancellation Using RLS Adaptive Filtering
PRODUCT: MATLAB;DSP System Toolbox
DESCRIPTION:
Use an RLS filter to extract useful information from a noisy signal. The information bearing signal is a sine wave that is corrupted by additive white Gaussian noise.


COMPONENT: dsp
EXAMPLENAME: ExportSignalsForSampleBasedProcessingExample
EXAMPLETITLE: Export Signals for Sample-Based Processing
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
The To Workspace (Simulink) and Triggered To Workspace blocks are the primary blocks for exporting signals of all dimensions from a Simulink model to the MATLAB workspace.


COMPONENT: dsp
EXAMPLENAME: CreateMultichannelSignalsByCombiningSingleChannelSignalsExample
EXAMPLETITLE: Combine Signals Using Matrix Concatenate Block
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
You can combine individual signals into signals of larger dimensions using the Matrix Concatenate block.


COMPONENT: dsp
EXAMPLENAME: BuildYourVectorQuantizerModelExample
EXAMPLETITLE: Build Your Vector Quantizer Model
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
In the previous section, you quantized your residual signal and reflection coefficients. The bit rate of your scalar quantization system was 64.4 kbits per second. This bit rate is higher than most modern speech coders. To accommodate a greater number of users in each channel, you need to lower this bit rate while maintaining the quality of your speech signal. You can use vector quantizers, which exploit the correlations between each sample of a signal, to accomplish this task.


COMPONENT: dsp
EXAMPLENAME: CompareThePerformanceOfSIMDCodeWithGeneratedPlainCCodeExample
EXAMPLETITLE: Compare the Performance of SIMD Code with Generated Plain C Code
PRODUCT: MATLAB;DSP System Toolbox;Simulink;Communications Toolbox
DESCRIPTION:
Consider this Simulink model that models a digital communication system. The model contains a root-raised cosine filter on the transmitter and the receiver side, a couple of FIR Interpolation and FIR Decimation blocks to increase and decrease the sample rate of the signal, respectively, and an additive white Gaussian noise (AWGN) communication channel to transmit the signal. The root-raised cosine filters on both sides perform matched filtering. The combined response of the two root-raised cosine filters forms a raised-cosine filter, which helps in minimizing the intersymbol interference (ISI). Due to matched filtering, the signal received at the output has a high signal to noise ratio (SNR) and low probability of error. To confirm, view the output in the constellation diagram that follows.


COMPONENT: dsp
EXAMPLENAME: EstimateThePowerSpectrumUsingTheSpectrumAnalyzerExample
EXAMPLETITLE: Estimate the Power Spectrum Using the Spectrum Analyzer
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
You can view the power spectrum of a signal using the Spectrum Analyzer block. The power spectrum is computed in real time and varies with the input signal, and with changes in the properties of the Spectrum Analyzer block. You can change the dynamics of the input signal and see what effect those changes have on the spectrum of the signal in real time.


COMPONENT: dsp
EXAMPLENAME: GenerateRandomSignalWithGaussianDistributionExample
EXAMPLETITLE: Generate Random Signal with Gaussian Distribution
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Open the GenerateGaussianSignal.slx model by clicking the Open Model button. The Random Source block in the model has the Distribution parameter set to Gaussian .


COMPONENT: dsp
EXAMPLENAME: SettingAFinalFrequencyValueForUnidirectionalSweepsExample
EXAMPLETITLE: Unidirectional Linear Sweep
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
In this example, the Chirp block outputs a unidirectional, linearly swept chirp signal. The Time Scope displays the signal output in the time domain and the Spectrum Analyzer displays the spectrogram in the frequency domain.


COMPONENT: dsp
EXAMPLENAME: ComputeMovingAverageOfNoisyStepSignalExample
EXAMPLETITLE: Compute Moving Average of Noisy Step Signal
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Compare the sliding window averaging method and the exponentially weighted averaging method in Simulink using the Moving Average block.


COMPONENT: dsp
EXAMPLENAME: AnalyzeYourModelExample
EXAMPLETITLE: Analyze Your Model
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
The following sections guide you through the process of calculating the channel latencies required for perfect wavelet reconstruction. This example uses the ex_wavelets model, but you can apply the process to perform perfect wavelet reconstruction in any model. Open the ex_wavelets model by clicking the Open Model button.


COMPONENT: dsp
EXAMPLENAME: CreateSignalsUsingSignalFromWorkspaceBlockExample
EXAMPLETITLE: Create Signals Using Signal From Workspace Block
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Frame-based processing can significantly improve the performance of your model by decreasing the amount of time it takes your simulation to run. This topic describes how to create a two-channel signal with a sample period of 1 second, a frame period of 4 seconds, and a frame size of 4 samples using the Signal From Workspace block.


COMPONENT: dsp
EXAMPLENAME: CreateSignalsUsingSineWaveBlockExample
EXAMPLETITLE: Create Signals Using Sine Wave Block
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Based on these settings, the Sine Wave block outputs three sinusoids with amplitudes 1, 3, and 2 and frequencies 100, 250, and 500 Hz, respectively. The sample period of 1/5000 is 10 times the highest sinusoid frequency, which satisfies the Nyquist criterion. The frame size is 64 for all sinusoids, and therefore, the output has 64 rows.


COMPONENT: dsp
EXAMPLENAME: FilterNoisySignalUsingSOSHighpassFilterInSimulinkExample
EXAMPLETITLE: Filter Noisy Signal Using Second-Order Section (SOS) Highpass Filter in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Filter a noisy sinusoidal signal using the Second-Order Section Filter block. Obtain the numerator and denominator coefficients of the SOS filter using the Highpass IIR Filter Design block.


COMPONENT: dsp
EXAMPLENAME: AcousticNoiseCancellationLMSExample
EXAMPLETITLE: Acoustic Noise Cancellation (LMS)
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Use the least mean square (LMS) algorithm to subtract noise from an input signal. The example uses a preconfigured Simulink® model. The LMS Filter block in the dspanc model models an adaptive filter that uses the reference signal at its Input port and the desired signal at the Desired port to automatically match the filter response. The LMS Filter block subtracts the filtered noise from the original signal. As the filter converges, the resultant error signal contains only the original signal.


COMPONENT: dsp
EXAMPLENAME: UseLogicAnalyzerWithMultipleModelBlockInstancesExample
EXAMPLETITLE: Choose Visible Instance of Multi-Reference Model Block
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
The Logic Analyzer can stream only a single instance of a multi-instance Model block. If the same model is opened across different windows, those models will share the same Logic Analyzer. This example shows how to select an instance of a multi-instance Model block for logging on the Logic Analyzer.


COMPONENT: dsp
EXAMPLENAME: SolveMatrixEquationsUsingBackwardSubstitutionExample
EXAMPLETITLE: Solve Matrix Equation Using Backward Substitution
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Use Backward Substitution block to solve a system of linear equations. Verify the solution using Matrix Multiply block.


COMPONENT: dsp
EXAMPLENAME: EstimateFrequencyDomainTransferFunctionOfSystemExample
EXAMPLETITLE: Estimate Frequency-Domain Transfer Function of System Using Random Excitation Input
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Use the Discrete Transfer Function Estimator block to estimate the frequency-domain transfer function of a system.


COMPONENT: dsp
EXAMPLENAME: FilterNoisySignalUsingSOSLowpassFilterInSimulinkExample
EXAMPLETITLE: Filter Noisy Signal Using Second-Order Section (SOS) Lowpass Filter in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Filter a noisy sinusoidal signal using the Second-Order Section Filter block. Obtain the numerator and denominator coefficients of the SOS filter using the Lowpass IIR Filter Design block.


COMPONENT: dsp
EXAMPLENAME: WWVDigitalReceiverSynchronizationAndDetectionExample
EXAMPLETITLE: WWV Digital Receiver - Synchronization and Detection
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
An implementation of a digital receiver that synchronizes to the time code information broadcast by radio station WWV and decodes it to display time information. The example uses the Simulink®, DSP System Toolbox™, and Stateflow® products with the MATLAB® Function block to achieve a simple noncoherent digital receiver.


COMPONENT: dsp
EXAMPLENAME: ComputeMovingVarianceOfNoisySquareWaveSignalExample
EXAMPLETITLE: Compute Moving Variance of Noisy Square Wave Signal
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Compare the sliding window variance method and the exponentially weighted variance method in Simulink using the Moving Variance block.


COMPONENT: dsp
EXAMPLENAME: BufferFrameInputsIntoOtherFrameInputsExample
EXAMPLETITLE: Buffer Frame Inputs into Other Frame Inputs
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
In the following example, a two-channel signal with frame size 4 is rebuffered to a signal with frame size 3 and frame period 2. Because of the overlap, the input sample period is not conserved, and the output sample period is 2/3:


COMPONENT: dsp
EXAMPLENAME: OpenTheModelExample
EXAMPLETITLE: Open the Model
PRODUCT: MATLAB;DSP System Toolbox;Simulink;Simulink Coder
DESCRIPTION:
Open the ex_codegen_dsp model. The model implements a simple adaptive filter to remove noise from a signal while simultaneously identifying a filter that characterizes the noise frequency content.


COMPONENT: dsp
EXAMPLENAME: DesignAndImplementTwoChannelFIRFilterBankInSimulinkExample
EXAMPLETITLE: Design and Implement Two-Channel FIR Filter Bank in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Use the FIR Halfband Decimator and FIR Halfband Interpolator blocks to implement a two-channel filter bank. This example uses an audio file input and shows that the power spectrum of the filter bank output does not differ significantly from the input. Play the output of the filter bank using the Audio Device Writer block.


COMPONENT: dsp
EXAMPLENAME: GenerateThreeChannelDiscreteImpulseBlockExample
EXAMPLETITLE: Generate Discrete Impulse with Three Channels
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Generate a discrete impulse signal with three channels and a data type of double . The Discrete Impulse block has the following settings:


COMPONENT: dsp
EXAMPLENAME: DetectThresholdCrossingsUsingEventCountComparatorBlockExample
EXAMPLETITLE: Detect Threshold Crossings Using Event Count Comparator Block
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Open the ex_eventcountcomp_ref model. The Event-Count Comparator block ( Event threshold = 3) detects two threshold crossings in the input to the Data port, one at sample 4 and one at sample 12.


COMPONENT: dsp
EXAMPLENAME: UnbufferFrameSignalsIntoSampleSignalsExample
EXAMPLETITLE: Unbuffer Frame Signals into Sample Signals
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
You can unbuffer multichannel signals of frame length greater than 1 into multichannel signals of frame length equal to 1 using the Unbuffer block. The Unbuffer block performs the inverse operation of the Buffer block's buffering process, where signals with frame length 1 are buffered into a signal with frame length greater than 1. The Unbuffer block generates an N-channel output containing one sample per frame from an N-channel input containing multiple channels per frame. The first row in each input matrix is always the first output.


COMPONENT: dsp
EXAMPLENAME: ThreePhaseFaultDetectionExample
DESCRIPTION: Detect faults in three-phase power transmission using the Deep Signal Anomaly Detector block.
EXAMPLETITLE:
Fault Detection and Localization in Three-Phase Power Transmission Using Deep Signal Anomaly Detector in Simulink

PRODUCT:
MATLAB;DSP System Toolbox;Simscape;Simscape Electrical;Signal Processing Toolbox;Deep Learning Toolbox


COMPONENT: dsp
EXAMPLENAME: ReadingDataFromAsyncBufferObjectExample
PRODUCT: MATLAB;DSP System Toolbox;Simulink
EXAMPLETITLE:
Why Does Reading Data from the dsp.AsyncBuffer Object Give a Dimension Mismatch Error in MATLAB Function Block?

DESCRIPTION:
Resolve the dimension mismatch error when you read data from an Async buffer inside the MATLAB function block.


COMPONENT: dsp
EXAMPLENAME: BasicAlgorithmicDelayExample
EXAMPLETITLE: Basic Algorithmic Delay
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
The Variable Integer Delay block is an example of a block with algorithmic delay. In the following example, you use this block to demonstrate this concept:


COMPONENT: dsp
EXAMPLENAME: SpeechEnhancementWithGainInFrequencyDomainExample
EXAMPLETITLE: Speech Enhancement with Gain in Frequency Domain
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Denoise a signal by applying selective gain on the signal in the frequency domain. Convert the denoised signal back into time domain and play the signal using Audio Device Writer.


COMPONENT: dsp
EXAMPLENAME: SolveMatrixEquationUsingForwardSubstitutionExample
EXAMPLETITLE: Solve Matrix Equation Using Forward Substitution
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Use Forward Substitution block to solve a system of linear equations. Verify the solution using Matrix Multiply block.


COMPONENT: dsp
EXAMPLENAME: TwoStageMultirateNarrowLowpassFilterExample
EXAMPLETITLE: Two-Stage Multirate Narrow Lowpass Filter
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Implement a two-stage multirate narrow band lowpass filter using FIR Decimation and FIR Interpolation blocks.


COMPONENT: dsp
EXAMPLENAME: GenerateRandomSignalWithUniformDistributionExample
EXAMPLETITLE: Generate Random Signal with Uniform Distribution
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Open the GenerateUniformSignal.slx model by clicking the Open Model button. The Random Source block in the model has the Distribution parameter set to Uniform . The minimum and maximum values of the uniform distribution are 1 and 3, respectively.


COMPONENT: dsp
EXAMPLENAME: BufferingInputWOverlapExample
EXAMPLETITLE: Buffering Input with Overlap
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Buffer a two-channel input using an Output buffer size of three and four and a Buffer overlap of one.


COMPONENT: dsp
EXAMPLENAME: CombineSignalsUsingMatrixConcatenateBlockExample
EXAMPLETITLE: Combine Signals Using Matrix Concatenate Block
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
You can combine individual signals into signals of larger dimensions using the Matrix Concatenate block. To combine signals, all signals must have the same frame rate and frame size.


COMPONENT: dsp
EXAMPLENAME: GenerateFrameBasedSineWavesBlockExample
EXAMPLETITLE: Generate Frame-Based Sine Waves
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Compares the different methods of generating frame-based sine waves from the Sine Wave block in DSP System Toolbox™.


COMPONENT: dsp
EXAMPLENAME: EstimatePowerSpectrumUsingTheSpectrumEstimatorBlockExample
EXAMPLETITLE: Estimate Power Spectrum Using the Spectrum Estimator Block
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Alternately, you can compute the power spectrum of the signal using the Spectrum Estimator block in the dspspect3 library. You can acquire the output of the spectrum estimator and store the data for further processing.


COMPONENT: dsp
EXAMPLENAME: ImplementAnFIRDecimatorInSimulinkExample
EXAMPLETITLE: Implement an FIR Decimator in Simulink
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
You can design and implement the FIR multirate filters in Simulink™ using the FIR Decimation, FIR Interpolation, and FIR Rate Conversion blocks.


COMPONENT: dsp
EXAMPLENAME: GenerateConstantRampSignalBlockExample
EXAMPLETITLE: Generate Constant Ramp Signal
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Generate a ramp signal using the Constant Ramp block. The Ramp length equals number of parameter allows you to specify input signal dimension that determines the length of the generated constant ramp signal.


COMPONENT: dsp
EXAMPLENAME: ContinuousTimeTransferFunctionEstimationExample
EXAMPLETITLE: Continuous-Time Transfer Function Estimation
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Use the Discrete Transfer Function Estimator block to estimate the magnitude and phase response of a continuous-time analog filter.


COMPONENT: dsp
EXAMPLENAME: ImportFrameBasedSignalFromWorkspaceBlockExample
EXAMPLETITLE: Import Two-Channel Signal From Workspace
PRODUCT: DSP System Toolbox;MATLAB;Simulink
DESCRIPTION:
Import a two-channel signal, A , from the MATLAB® workspace into the Simulink® model using the Signal From Workspace block. Use the To Workspace block to write the imported data to the MATLAB workspace. In this model, the To Workspace block writes slightly modified data to the MATLAB workspace.


COMPONENT: dsp
EXAMPLENAME: RealTimeECGQRSDetectionExample
EXAMPLETITLE: Real-Time ECG QRS Detection
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Detect the QRS complex of an electrocardiogram (ECG) signal in real time. The example uses Model-Based design to develop, test, deploy the algorithm.


COMPONENT: dsp
EXAMPLENAME: ImportVectorSignalsForSampleBasedProcessingExample
EXAMPLETITLE: Import Vector Signals for Sample-Based Processing
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
The Signal From Workspace block generates a vector signal for sample-based processing when the variable or expression in the Signal parameter is a matrix and the Samples per frame parameter is set to 1. Each column of the input matrix represents a different channel. Beginning with the first row of the matrix, the block outputs one row of the matrix at each sample time. Therefore, if the Signal parameter specifies an M-by-N matrix, the output of the Signal From Workspace block is M 1-by-N row vectors representing N channels.


COMPONENT: dsp
EXAMPLENAME: SpecifyFreqRespOfTheFrequencyDomainFIRFilterSimulinkExample
EXAMPLETITLE: Specify Frequency Response of Frequency-Domain FIR Filter
PRODUCT: MATLAB;DSP System Toolbox;Simulink
DESCRIPTION:
Specify the numerator coefficients of the frequency-domain FIR filter in the frequency domain. Filter the input signal using the overlap-add method. Compare the frequency-domain FIR filter output to the corresponding time-domain FIR filter output.


COMPONENT: dsp_hdlcoder
EXAMPLENAME: DiscreteFIRStreamingHDLExample
EXAMPLETITLE: Area Reduction of Multichannel Filter Subsystem
PRODUCT: MATLAB;DSP System Toolbox;HDL Coder;Simulink;Fixed-Point Designer
DESCRIPTION:
To reduce the number of multipliers in the HDL implementation of a multichannel filter and surrounding logic, use the StreamingFactor HDL Coder™ optimization.


COMPONENT: dsp_hdlcoder
EXAMPLENAME: DiscreteFIRSharingHDLExample
EXAMPLETITLE: Area Reduction of Filter Subsystem
PRODUCT: MATLAB;DSP System Toolbox;Simulink;HDL Coder;Fixed-Point Designer
DESCRIPTION:
To reduce the number of multipliers in the HDL implementation of a multifilter design, use the SharingFactor HDL Coder™ optimization.


COMPONENT: dsp_hdlcoder
EXAMPLENAME: ProgrammableFIRFilterForFPGAExample
EXAMPLETITLE: Programmable FIR Filter for FPGA
PRODUCT: MATLAB;Simulink;DSP HDL Toolbox
DESCRIPTION:
Implement a programmable FIR filter for hardware. You can program the filter to the required response by loading the coefficients into internal registers using a memory-style interface.


COMPONENT: dsp_hdlcoder
EXAMPLENAME: AudioFilterMultipleAXI4StreamChannelsZedBoardExample
EXAMPLETITLE: Running Audio Filter with Multiple AXI4-Stream Channels on ZedBoard
PRODUCT: MATLAB;DSP HDL Toolbox;HDL Coder;Embedded Coder
DESCRIPTION:
Model an audio system with multiple AXI4-Stream channels and deploy it on a ZedBoard™ by using an audio reference design.


COMPONENT: dsp_hdlcoder
EXAMPLENAME: HDLImplementationOfDDCForLTEExample
EXAMPLETITLE: Implement Digital Downconverter for FPGA
PRODUCT: MATLAB;DSP HDL Toolbox;HDL Coder;Simulink
DESCRIPTION:
Design a digital downconverter (DDC) for radio communication applications such as LTE, and generate HDL code.


COMPONENT: dsp_hdlcoder
EXAMPLENAME: HDLImplementationOfDUCForLTEExample
EXAMPLETITLE: Implement Digital Upconverter for FPGA
PRODUCT: MATLAB;HDL Coder;DSP HDL Toolbox;Simulink
DESCRIPTION:
Design a digital upconverter (DUC) for radio communication applications such as LTE, and generate HDL code.


COMPONENT: dsphdl
EXAMPLENAME: FrequencyDomainFilteringInHDLExample
EXAMPLETITLE: Frequency-Domain Filtering in HDL
PRODUCT: MATLAB;DSP HDL Toolbox;Simulink;Fixed-Point Designer
DESCRIPTION:
Implement a filter in the frequency domain. The filter is built with the FFT and IFFT blocks from DSP HDL Toolbox™.


COMPONENT: dsphdl
EXAMPLENAME: OptimProgFIRFilterResourcesExample
EXAMPLETITLE: Optimize Programmable FIR Filter Resources
PRODUCT: MATLAB;Simulink;DSP HDL Toolbox
DESCRIPTION:
Implement a programmable FIR filter that optimizes multiplier resources for patterns in coefficients.


COMPONENT: dsphdl
EXAMPLENAME: HDLSynthesizeAndChannelizeAudioExample
EXAMPLETITLE: HDL Implementation of Four Channel Synthesizer and Channelizer
PRODUCT: MATLAB;DSP HDL Toolbox;Simulink
DESCRIPTION:
Synthesize four stereo signals into a broadband signal and split the signal back into the individual narrowband signals.


COMPONENT: dsphdl
EXAMPLENAME: GigasamplepersecondCorrelatorAndPeakDetectorExample
EXAMPLETITLE: Gigasamples-per-Second Correlator and Peak Detector
PRODUCT: MATLAB;DSP HDL Toolbox
DESCRIPTION:
Implement a high-throughput correlator and peak detector suitable for LiDAR and mm-wave RADAR applications on FPGA.


COMPONENT: dsphdl
EXAMPLENAME: FractionalDelaysUsingFarrowFiltersExample
EXAMPLETITLE: Fractional Delay Filters
PRODUCT: MATLAB;DSP HDL Toolbox
DESCRIPTION:
Implement fractional delay filters for hardware, including a variable fractional delay filter that uses a Farrow algorithm.


COMPONENT: dsphdl
EXAMPLENAME: CalculateMeanSquareErrorUsingLMSFilterBlockExample
EXAMPLETITLE: Calculate Mean Square Error Performance Using LMS Filter
PRODUCT: MATLAB;DSP HDL Toolbox;Simulink
DESCRIPTION:
How use the LMS Filter block to calculate the mean square error performance in additive white Gaussian noise (AWGN). The block supports scalar and vector inputs of type real or complex. You can generate the HDL code from the LMSFilter subsystem in this Simulink® model.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeUsingSmallMatrixCRLExample
PRODUCT: MATLAB;Embedded Coder
EXAMPLETITLE:
Generate Code to Optimize Performance of a Small Matrix Operation for Processor-Specific Intrinsic Function

DESCRIPTION:
In this section, you generate code using the code replacement library that you created in the first two sections of this example. A nonscalar small matrix multiplication operation is replaced with a call to a custom function in the generated code. This example does not provide an implementation of the custom function. Write your own implementation.


COMPONENT: ecoder
EXAMPLENAME: DoWhileLoopExample
EXAMPLETITLE: Do While Loop
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Use a While Iterator Subsystem block or Stateflow Chart to create a do while loop in the generated code.


COMPONENT: ecoder
EXAMPLENAME: OptimizeSIMDCodeByPerformingFusedMultiplyAddOperationsExample
EXAMPLETITLE: Optimize SIMD Code by Performing Fused Multiply Add Operations
PRODUCT: Embedded Coder;Simulink
DESCRIPTION:
For processors that support FMA instructions, improve execution efficiency by performing fused multiply-add operations.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeUsingBlasCRLExample
EXAMPLETITLE: Convert a Matrix Multiplication Operation to MathWorks BLAS Through Code Replacement
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
In this section, you generate code using the code replacement library that you created in the first two sections of this example. A floating-point matrix/matrix multiplication operation is replaced with a custom multiplication function dgemm in the generated code. This example does not provide an implementation function. Write your own implementation.


COMPONENT: ecoder
EXAMPLENAME: TunableParameterExpressionsSaturationExample
EXAMPLETITLE: Remove Code from Tunable Parameter Expressions That Saturate Against Integer Overflow
PRODUCT: MATLAB;Embedded Coder;Simulink
DESCRIPTION:
Remove code that prevents integer overflow of tunable expression parameters for efficiency benefits.


COMPONENT: ecoder
EXAMPLENAME: OpenModelToGenerateCodeUsingMathCodeReplacementLibraryExample
EXAMPLETITLE: Generate Code by Using Math Code Replacement Library
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
In this section, you generate code using the code replacement library that you created in the first two sections of this example. A math function sin is replaced with a call to a custom function in the generated code. This example does not provide an implementation function. Write your own implementation.


COMPONENT: ecoder
EXAMPLENAME: BitwiseOperationsExample
EXAMPLETITLE: Bitwise Operations
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Perform bitwise operations using the Bitwise Operator block, a Stateflow Chart, or MATLAB Function block.


COMPONENT: ecoder
EXAMPLENAME: SILPILVerificationExample
EXAMPLETITLE: Test Generated Code with SIL and PIL Simulations
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Use software-in-the-loop (SIL) and processor-in-the-loop (PIL) simulations to test numerical equivalence between model components and generated code.


COMPONENT: ecoder
EXAMPLENAME: ConsolidateRedundantIfElseStatementsExample
EXAMPLETITLE: Optimize Generated Code by Consolidating Redundant If-Else Statements
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
The code generator optimizes the generated code by combining if-else statements that share the same condition.


COMPONENT: ecoder
EXAMPLENAME: SwitchExample
EXAMPLETITLE: Switch
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Use a Switch Case block or MATLAB Function block to create an switch statement in the generated code.


COMPONENT: ecoder
EXAMPLENAME: PMSMFieldOrientedControlExample
EXAMPLETITLE: Field-Oriented Control of Permanent Magnet Synchronous Machine
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder;Stateflow;Simscape;Simscape Electrical
DESCRIPTION:
Simulate motor control system, generate controller code, and use PIL simulation to test numerical equivalence and profile code execution times.


COMPONENT: ecoder
EXAMPLENAME: DataObjectWizardDemoExample
EXAMPLETITLE: Create Data Objects for Code Generation with Data Object Wizard
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder;Stateflow
DESCRIPTION:
Use the Data Object Wizard to create data objects, which enable you to specify code generation options for individual data items.


COMPONENT: ecoder
EXAMPLENAME: DeployRateComponentConfiguredForServiceInterfaceCodeGenExample
EXAMPLETITLE: Deploy Single-Rate, Rate-Based Component Configured for C Service Interface Code Generation
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Develop a rate-based model as a component that includes service interface support for interacting with target platform software.


COMPONENT: ecoder
EXAMPLENAME: ReduceMemoryUsageForModelsContainingReferencedModelsExample
EXAMPLETITLE: Reduce Memory Usage for Models Containing Referenced Models
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Reduce RAM usage for a referenced model by generating optimized code that reuses buffers or generates reusable temporary buffers to hold referenced model outputs.


COMPONENT: ecoder
EXAMPLENAME: DeployMRateComponentConfigForCServiceInterfaceCodeGenExample
EXAMPLETITLE: Deploy Multirate Rate-Based Component Configured for C Service Interface Code Generation
PRODUCT: MATLAB;Embedded Coder;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Develop a multirate rate-based model as a component that includes service interface support for interacting with target platform software.


COMPONENT: ecoder
EXAMPLENAME: RemoveInitializationCodeForLocalVariablesSetToZeroExample
EXAMPLETITLE: Control Generation of Initialization Code for Local Variables Set to Zero
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
By default, the code generator does not explicitly initialize local variables to zero. This produces more efficient code, but violates some coding standards such as MISRA C++:2008 Rule 0-1-4. This example shows how to disable this optimization to remove initialization code from local variables set to zero.


COMPONENT: ecoder
EXAMPLENAME: ForLoopExample
EXAMPLETITLE: For Loop
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Use a For-Iterator Subsystem block, Stateflow Chart, or MATLAB Function block to create a for loop in the generated code.


COMPONENT: ecoder
EXAMPLENAME: SeparateRateTranstionBlockCodeAndDataExample
EXAMPLETITLE: Separate Rate Transition Block Code and Data from Algorithm Code and Data
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
You can specify whether the code generator inlines code and data it produces for Rate Transition blocks with model code or places the code and data in separate functions that the model code calls. You control this by selecting the Rate Transition block code parameter. Separating Rate Transition block code and data from algorithm code and data enables you to independently analyze, optimize, and test Rate Transition block and algorithm code. By default, Rate Transition block code is set inline with algorithm code and data. You can separate the code and data so that the generated code contains separate get and set functions that the model_step functions call and a dedicated structure for state data. The generated code also contains separate start and initialize functions that the model_initialize function calls.


COMPONENT: ecoder
EXAMPLENAME: CppGetMethodNameForInitializeFcnForModelExample
EXAMPLETITLE: Get the Method Name for the Initialize Function for a Model
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Open the model. To access the CodeMappingCPP object associated with the model, use the coder.mapping.api.get function.


COMPONENT: ecoder
EXAMPLENAME: ShareGlobalVarsBetwComponentsExample
EXAMPLETITLE: Establish Data Ownership in a Model Hierarchy
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
In the generated code, place the definitions of global variables with the components that define them.


COMPONENT: ecoder
EXAMPLENAME: UserDefinedDataTypesDemoExample
EXAMPLETITLE: Define Abstract Numeric Types and Rename Types
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder;Stateflow
DESCRIPTION:
User-defined types, consisting of numeric and alias types. Numeric types allow you to define abstract numeric types, which is particularly useful for fixed-point types. Alias types allow you to rename types, which allows you create a relationship for types.


COMPONENT: ecoder
EXAMPLENAME: UseSubsystemVariantsCPreprocessorConditionalsExample
EXAMPLETITLE: Use Variant Subsystem to Generate Code That Uses C Preprocessor Conditionals
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Use variant subsystems to generate C preprocessor conditionals that control which child subsystem of the variant subsystem is active in the generated code.


COMPONENT: ecoder
EXAMPLENAME: ImproveAccuracyOfTimeValuesReadByEntryPointFunctionsExample
EXAMPLETITLE: Improve Accuracy of Time Values Read by Generated Entry-Point Functions
PRODUCT: MATLAB;Embedded Coder;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Improve the accuracy of time values read by generated entry-point functions by configuring the model clock resolution.


COMPONENT: ecoder
EXAMPLENAME: CreateANamedFixedPointDataTypeInTheGeneratedCodeExample
EXAMPLETITLE: Create a Named Fixed-Point Data Type in the Generated Code
PRODUCT: Embedded Coder;Fixed-Point Designer;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Create and name a fixed-point data type in generated code. You can use the name of the type to specify parameter and signal data types throughout a model and in generated code.


COMPONENT: ecoder
EXAMPLENAME: ConfigGenCodeAccdingICDInterExample
EXAMPLETITLE: Configure Generated Code According to Interface Control Document Specifications
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder;Stateflow
DESCRIPTION:
Configure code generation settings for a model according to specifications from an interface control document.


COMPONENT: ecoder
EXAMPLENAME: OptimizeGeneratedCodeForFixedPointDataOperationsExample
EXAMPLETITLE: Optimize Generated Code for Fixed-Point Data Operations
PRODUCT: Embedded Coder;Fixed-Point Designer;MATLAB;Simulink
DESCRIPTION:
The code generator optimizes fixed-point operations by replacing expensive division operations with highly efficient product operations.


COMPONENT: ecoder
EXAMPLENAME: GenerateLocalVariablesExploreExampleModelExample
EXAMPLETITLE: Explore Example Model
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Generate local variables for signals and compares it to generating global variables for the same signals.


COMPONENT: ecoder
EXAMPLENAME: ConfiigDefaultDataAndFuncCodeGenProgExample
EXAMPLETITLE: Configure Default Data and Function Code Generation Programmatically
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Configure default data and function code generation for example model ConfigurationInterface. The example uses the default mapping programming interface to specify code generation requirements for model data and functions. Use that interface to automate the configuration, or if you prefer to configure models programmatically. For information about configuring the default data and function code generation by using the Code Mappings editor, see Configure Default Code Generation for Categories of Model Data and Functions.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeUsingAddSubCodeReplacementLibraryExample
EXAMPLETITLE: Generate Code Using Addition and Subtraction Operator Code Replacement Library
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
In this section, you generate code using the code replacement library that you created in the first two sections of this example. The generated code contains the implementation function signature that modifies an addition operator. For this example, the addition operator contains the Cast before operation parameter. This example does not provide an implementation function. You should write the implementation function that contains the optimization that you want to see in the generated code.


COMPONENT: ecoder
EXAMPLENAME: OpenECDictionaryForDataAccessByFunctionExample
EXAMPLETITLE: Open Embedded Coder Dictionary
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
You can define and apply a storage class to root-level inports, root-level outports, and model parameters so they can be accessed by customizable get and set functions. Such customization can be useful, for example, to abstract layers of software, gain access to data from an external file or to control access to critical sections of code.


COMPONENT: ecoder
EXAMPLENAME: RemoveResetAndDisableFunctionsExample
EXAMPLETITLE: Remove Reset and Disable Functions from the Generated Code
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Remove unreachable (dead-code) instances of the reset and disable functions from the generated code for ERT-based systems that include model referencing hierarchies.


COMPONENT: ecoder
EXAMPLENAME: CompareGeneratedHalideCodeToPlainCCodeExample
EXAMPLETITLE: Compare Generated Halide Code to Plain C++ Code
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Matrix multiplication is a crucial operation in numerous applications. This example uses the model MatrixMultiply that has a Matrix Multiply block. The Matrix Multiply block has input signals with dimension sizes 512 and data type int8 .


COMPONENT: ecoder
EXAMPLENAME: DeployComponentWithCServiceInterfaceCodeGenExample
EXAMPLETITLE: Deploy Export-Function Component Configured for C Service Interface Code Generation
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Develop an export-function model as a component that includes service interface support for interacting with target platform software.


COMPONENT: ecoder
EXAMPLENAME: RelationalAndLogicalOperatorsExample
EXAMPLETITLE: Relational and Logical Operators
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Implement relational and logical operators using Simulink blocks, Stateflow Charts, and MATLAB Function blocks.


COMPONENT: ecoder
EXAMPLENAME: ApplyCustomNamingConventionsToIdentifiersExample
EXAMPLETITLE: Apply Custom Naming Conventions to Identifiers
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Apply uniform naming rules for Simulink® data objects, including signals, parameters, and data store memory variables.


COMPONENT: ecoder
EXAMPLENAME: ReusableCodeInterfaceExample
EXAMPLETITLE: Generate Reentrant, Multi-Instance Code
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Configure a model for reentrant, multi-instance code generation. Multiple programs can use reentrant code simultaneously. When you configure a model for reentrancy, the execution (step) entry-point function uses root-level input and output arguments instead of global data structures. After examining the configuration settings, generate and review the generated code.


COMPONENT: ecoder
EXAMPLENAME: DivisionByZeroForFixedpointDataExample
EXAMPLETITLE: Remove Code That Guards Against Division Exceptions for Integers and Fixed-Point Data
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Optimize the generated code by removing code that protects against division by zero and overflows in division INT_MIN/-1 operations for integers and fixed-point data.


COMPONENT: ecoder
EXAMPLENAME: PassReusableSubsysOutputsAsIndividualArgsExample
EXAMPLETITLE: Optimize Generated Code by Passing Reusable Subsystem Outputs as Individual Arguments
PRODUCT: Embedded Coder;MATLAB;Simulink;Simulink Coder
DESCRIPTION:
The code generator eliminates data copies from local variables back to global block I/O structures by passing reusable subsystem outputs as individual arguments instead of as a pointer to a structure stored in global memory.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeUsingLookupTableCodeReplacementLibraryExample
EXAMPLETITLE: Generate Code by Using Lookup Table Code Replacement Library
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
In this section, you generate code using the code replacement library that you created in the first two sections of this example. A Lookup table function is replaced with a call to a custom function in the generated code. This example does not provide an implementation function. Write your own implementation.


COMPONENT: ecoder
EXAMPLENAME: MemoryMappingEcoderExample
EXAMPLETITLE: Generate Code That Dereferences Data from a Literal Memory Address
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Generate code that reads the value of a signal by dereferencing a memory address that you specify. With this technique, you can generate a control algorithm that interacts with memory that your hardware populates (for example, memory that stores the output of an analog-to-digital converter in a microcontroller).


COMPONENT: ecoder
EXAMPLENAME: GenerateCDataTransferServiceInterfaceForCompDeploymentExample
EXAMPLETITLE: Generate C Data Transfer Service Interface Code for Component Deployment
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Generate calls to target platform data transfer service functions to exchange data between callable entry-point functions generated from a component model.


COMPONENT: ecoder
EXAMPLENAME: AccessLegacyDataUsingGetAndSetFunctionsExample
EXAMPLETITLE: Access Legacy Data Using Get and Set Functions
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Generate code that interfaces with legacy code by using specialized get and set functions to access data.


COMPONENT: ecoder
EXAMPLENAME: RtwdemoImportStructExample
EXAMPLETITLE: Access Structured Data Through a Pointer That External Code Defines
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Generate code that accesses parameter data through a structure pointer that handwritten code defines.


COMPONENT: ecoder
EXAMPLENAME: ConvertDataCopiesToPointerAssignmentsExample
EXAMPLETITLE: Convert Data Copies to Pointer Assignments
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
The code generator optimizes generated code for vector signal assignments by trying to replace for loop controlled element assignments and memcpy function calls with pointer assignments.


COMPONENT: ecoder
EXAMPLENAME: DataCopyReductionForDataStoreReadAndDataStoreWriteBlocksExample
EXAMPLETITLE: Data Copy Reduction for Data Store Read and Data Store Write Blocks
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
The code generator attempts to eliminate data copies for Data Store Read and Data Store Write blocks.


COMPONENT: ecoder
EXAMPLENAME: ControlFilePackagingOfGeneratedEntryPointFcnsAndSLFcnsExample
EXAMPLETITLE: Control File Packaging of Generated Entry-Point Functions and Simulink Functions
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Specify custom filenames for entry-point functions and Simulink® functions using function customization templates. Use custom filenames to group related functions together in generated code.


COMPONENT: ecoder
EXAMPLENAME: GenerateCCodeFromSimulinkModelsExample
EXAMPLETITLE: Generate C Code from Simulink Models
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Generate, test, and deploy C code optimized for an embedded system from a model that represents a discrete-time control system.


COMPONENT: ecoder
EXAMPLENAME: CppCreateEnvironmentToConfigureCppCodeMappingsExample
EXAMPLETITLE: Create Environment to Configure C++ Code Mappings for Model
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Open the model CppClassRateBased, and create the environment for configuring model data and functions for code generation by using the coder.mapping.utils.create function.


COMPONENT: ecoder
EXAMPLENAME: CppClassGenerateMultiExpFuncExample
EXAMPLETITLE: Generate C++ Class Interface from Multi-Instance Export-Function Model
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Example of code generation of a C++ class interface for multiple instances of an Export-Function model.


COMPONENT: ecoder
EXAMPLENAME: ModelAdvisorIEC61508Example
EXAMPLETITLE: Develop a Model That Complies with the IEC 61508 Standard
PRODUCT: Embedded Coder;MATLAB;Simulink;Simulink Coder;Simulink Check
DESCRIPTION:
Use Model Advisor checks for the IEC 61508 standard to develop a model and code that comply with the standard.


COMPONENT: ecoder
EXAMPLENAME: ExploreExampleModelCustomStorageClassesExample
EXAMPLETITLE: Explore Example Model
PRODUCT: MATLAB;MATLAB Coder;Simulink;Simulink Coder;Embedded Coder
DESCRIPTION:
Model for example that shows how to control generatd code by defining a storage class in a user-defined data class package and applying the storage class for data objects.


COMPONENT: ecoder
EXAMPLENAME: CppFindModelFcnsUnsetMethodNameExample
EXAMPLETITLE: Find All Model Functions with an Unset Method Name
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
You can use the find function to find all model elements of a specific category in the code mappings.


COMPONENT: ecoder
EXAMPLENAME: VariantModelBlocksControlledByCPreprocessorConditionalsExample
EXAMPLETITLE: Use Variant Models to Generate Code That Uses C Preprocessor Conditionals
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Use model variants to generate code that uses preprocessor conditionals to control which code is linked into the embedded executable.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeGenerationReportProgrammaticallyExample
EXAMPLETITLE: Configure and Generate Code Generation Report Programmatically
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
You can programmatically generate, open, and close an HTML code generation report at the MATLAB® command line using the coder.report.generate, coder.report.open, and coder.report.close functions respectively. When you generate the report, you can configure it rather than tie the report configuration to the model configuration set. If you do not change the model after generating code, you can generate a code generation report without regenerating the code.


COMPONENT: ecoder
EXAMPLENAME: IfElseExample
EXAMPLETITLE: If-Else
PRODUCT: Embedded Coder;MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Use a Switch block, a Stateflow Chart, or MATLAB Function block to create an if-else statement in the generated code.


COMPONENT: ecoder
EXAMPLENAME: ExternalCFunctionsExample
EXAMPLETITLE: External C Functions
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Integrate legacy C functions in the generated code by either creating an S-function or making a call to an external C function.


COMPONENT: ecoder
EXAMPLENAME: DataTypeConversionExample
EXAMPLETITLE: Data Type Conversion
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Create a data type conversion using a Data Type Conversion block, Stateflow Chart, or MATLAB Function block.


COMPONENT: ecoder
EXAMPLENAME: ConfigureDataInterfaceFeaturedExample
EXAMPLETITLE: Configure Model Data Interface for C Code Generation
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Configure data elements in a model, such as block parameters and signal lines, so that corresponding variables appear in generated code.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeForASimulinkFunctionAndFunctionCallerExample
EXAMPLETITLE: Generate Code for Simulink Function and Function Caller
PRODUCT: MATLAB;Embedded Coder;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
How to generate C code for Simulink Function and Function Caller blocks and displays the relevant generated code.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeFromAnSFunctionBlockWithDimensionVariantsExample
EXAMPLETITLE: Generate Code from an S-Function Block with Dimension Variants
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
The model ex_msymbdims_sfcn_one contains an S-function that subtracts the symbolic dimension B from a symbolic input dimension, A + B . The model supports forward propagation because the symbolic dimensions of the output ports are set. The model does not support backward propagation of symbolic dimensions because the compiled symbolic dimensions of the input ports are not set.


COMPONENT: ecoder
EXAMPLENAME: WhileLoopExample
EXAMPLETITLE: While Loop
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Use a White Iterator Subsystem block, Stateflow Chart, or MATLAB Function block to create a while loop in the generated code.


COMPONENT: ecoder
EXAMPLENAME: GettingStartedWithAUTOSARCodeGenerationExample
EXAMPLETITLE: Develop a Model That Complies with the AUTOSAR Standard
PRODUCT: AUTOSAR Blockset;Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Generate AUTOSAR-compliant C code and export AUTOSAR XML (ARXML) descriptions from a Simulink® model.


COMPONENT: ecoder
EXAMPLENAME: ModelExplicitFuncInvocationWithAtomicSubsysExample
EXAMPLETITLE: Generate Code for Atomic Subsystems
PRODUCT: Embedded Coder;MATLAB;Simulink;Simulink Coder
DESCRIPTION:
A model designed and configured for deploying embedded system component code that is generated from a model that is partitioned into multiple atomic subsystems. The subsystems execute at different rates. The multirate top model is configured for C data interface code generation. You integrate the generated source code for each subsystem with other code, including an external scheduler, that runs in a target environment.


COMPONENT: ecoder
EXAMPLENAME: GenerateCParamServiceInterfaceCodeForComponentDeploymentExample
EXAMPLETITLE: Generate C Parameter Tuning Service Interface Code for Component Deployment
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Configure a target platform parameter tuning service to change parameter values while generated function code executes.


COMPONENT: ecoder
EXAMPLENAME: ImportParamCondCompiledDimLengthsExample
EXAMPLETITLE: Import Parameter Data with Conditionally Compiled Dimension Length
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Generate code that imports an array parameter whose dimension lengths your external code sets with macros ( #define ).


COMPONENT: ecoder
EXAMPLENAME: GetMetadataAboutServiceInterfaceExample
EXAMPLETITLE: Get Metadata About Service Interface
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Obtain metadata about the generated service interface by using the code descriptor programming interface.


COMPONENT: ecoder
EXAMPLENAME: GeneratePreprocessorConditionalsExample
EXAMPLETITLE: Conditional Inclusions (#if / #endif)
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Include preprocessor conditionals in your generated code by implementing variant blocks in your model.


COMPONENT: ecoder
EXAMPLENAME: GenerateSenderReceiverCInterfaceCodeComponentDeploymentExample
EXAMPLETITLE: Generate Sender and Receiver C Interface Code for Component Deployment
PRODUCT: MATLAB;Embedded Coder;Simulink;MATLAB Coder;Simulink Coder
DESCRIPTION:
Generate sender and receiver service functions to send and receive data to and from the target environment by using environment-specific data communication methods. Use data communication methods that match the needs of the target environment. For more information about data communication methods, see Data Communication Methods.


COMPONENT: ecoder
EXAMPLENAME: FlexibleStorageClassForDifferentModelHierarchyContextsExample
EXAMPLETITLE: Flexible Storage Class for Different Model Hierarchy Contexts
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Define and apply a storage class that uses different code generation settings for single-instance data and multi-instance data.


COMPONENT: ecoder
EXAMPLENAME: ConcurrentExecutionOnSymmetricMulticoreCPUPlatformsExample
EXAMPLETITLE: Model Multicore Concurrent Tasking Application
PRODUCT: Embedded Coder;MATLAB;Simulink;Simulink Coder
DESCRIPTION:
A model designed and configured for generating embedded system code intended to execute as an application in a symmetric multicore, multitasking target environment. The application algorithm is captured as a multirate top model that is configured for C data interface code generation.


COMPONENT: ecoder
EXAMPLENAME: SingleCoreMultitaskingPlatformExecutionExample
EXAMPLETITLE: Model Single-Core, Rate-Monotonic Multitasking Application
PRODUCT: Embedded Coder;MATLAB;Simulink;Simulink Coder
DESCRIPTION:
A model designed and configured for generating embedded system code intended to execute as an application in a single-core, multitasking target environment. The application algorithm is captured as a multirate top model that is configured for C data interface code generation. The model simulates and the generated code executes based on the model configuration and a rate monotonic scheduling algorithm.


COMPONENT: ecoder
EXAMPLENAME: ConfigCppFunctionInterfaceForScopedSimulinkFunctionBlockExample
EXAMPLETITLE: Configure Generated C++ Function Interface for Exported Scoped Simulink Function Block
PRODUCT: MATLAB;Embedded Coder;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
How to customize the C++ function interface generated for an exported, scoped Simulink Function block.


COMPONENT: ecoder
EXAMPLENAME: GenerateCMeasureServiceInterfaceCodeForCompDeploymentExample
EXAMPLETITLE: Generate C Measurement Service Interface Code for Component Deployment
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Configure a target platform measurement service to monitor signal, state, and data store values while generated function code executes.


COMPONENT: ecoder
EXAMPLENAME: CustomFunctionCodeReplacementExample
EXAMPLETITLE: Generate Code by Using Custom Function Code Replacement
PRODUCT: MATLAB;Embedded Coder
DESCRIPTION:
Generate code using the code replacement library that you previously created. A custom C function that is called in a MATLAB Function block is replaced with a call to a different custom function in the generated code.


COMPONENT: ecoder
EXAMPLENAME: MultirateModelingInMultitaskingModeVxWorksOSExample
EXAMPLETITLE: Multirate Modeling in Multitasking Mode (VxWorks® OS)
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Generates code for a multirate discrete-time model configured for a multitasking operating system target (VxWorks®). The model contains two sample times. Inport block 1 and Inport block 2 specify 1-second and 2-second sample times, respectively, which are enforced by the setting of model configuration parameter Periodic sample time constraint . The solver is set for multitasking operation, which means a Rate Transition block is required to ensure that data integrity is enforced when the 1-second task preempts the 2-second task. Simulink® and the code generator enforce proper rate transitions. This model specifies an explicit Rate Transition block. Alternatively, you can instruct Simulink® to insert this block for you by setting model configuration parameter Automatically handle rate transition for data transfer .


COMPONENT: ecoder
EXAMPLENAME: ConfigureFunctionInterfaceForScopedSimulinkFunctionBlockExample
EXAMPLETITLE: Configure Generated C Function Interface for Exported Scoped Simulink Function Block
PRODUCT: MATLAB;Embedded Coder;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
How to customize the C function interface generated for an exported, scoped Simulink Function block.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeUsingEmbeddedCoderExample
EXAMPLETITLE: Generate Code Using Embedded Coder
PRODUCT: Embedded Coder;MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Select a target for a Simulink model, configure options, generate C code for embedded systems, and view generated files.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeByUsingABlockReplacementLibraryExample
EXAMPLETITLE: Generate Code by Using a Block Replacement Library
PRODUCT: MATLAB;Embedded Coder;DSP System Toolbox
DESCRIPTION:
In this section, you generate code by using the code replacement library that you created in the first section of this example. The code generator replaces code from the Discrete FIR Filter block with calls to custom initialization and output functions in the generated code.


COMPONENT: ecoder
EXAMPLENAME: GenerateCodeForAModelWithDimensionVariantsExample
EXAMPLETITLE: Symbolic Dimension Variants
PRODUCT: Embedded Coder;MATLAB;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Use symbolic dimension variants to simulate various sets of dimension choices without regenerating code for every set. Set up your model with dimensions that you specify as symbols in blocks and data objects. These symbols propagate throughout the model during simulation, and then go into the generated code. Modeling constraints for symbols during simulation (for example, C=A+B) are output as preprocessor conditionals in either the model.h or the model _types.h file.


COMPONENT: ecoder
EXAMPLENAME: GenerateCTimerServiceInterfaceCodeForComponentDeploymentExample
EXAMPLETITLE: Generate C Timer Service Interface Code for Component Deployment
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Generate calls to target platform timer service functions to get the value of the target environment function clock tick.


COMPONENT: ecoder
EXAMPLENAME: TransformModelToVariantSystemUsingModelTransformerExample
EXAMPLETITLE: Transform Model to Variant System Using Model Transformer
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Check
DESCRIPTION:
Use the Model Transformer app to transform a model into a variant system. The example uses the model ControlFlowOptimization. This model has three Switch blocks. The control input to these Switch blocks is the Simulink.Parameter cond. The Model Transformer dialog box and this example refer to cond as a system constant.


COMPONENT: faultanalyzer
EXAMPLENAME: DetectionLogicAircraftElevatorExample
EXAMPLETITLE: Verify Fault Detection Logic in Aircraft Elevator Control System
PRODUCT: MATLAB;Simulink Fault Analyzer;Simulink;Stateflow;Requirements Toolbox
DESCRIPTION:
Use conditionals to verify that fault mitigation logic deploys and verify controller behavior in an FMEA.


COMPONENT: faultanalyzer
EXAMPLENAME: FaultAnalyzerIntroExample
EXAMPLETITLE: Open the Example Model
PRODUCT: MATLAB;Simulink Fault Analyzer;Simulink
DESCRIPTION:
Takes a sine wave and checks when it is greater than or equal to 1.25 . You can view the simulation results in the Scope block. The model does not include faults. Open the model to get started.


COMPONENT: faultanalyzer
EXAMPLENAME: CustomCallbacksAnalysisExample
EXAMPLETITLE: Add Flags by Using Multiple Analysis Callbacks
PRODUCT: MATLAB;Simulink Fault Analyzer;Simulink;Stateflow;Requirements Toolbox
DESCRIPTION:
Use custom callbacks in a Safety Analysis Manager spreadsheet. The spreadsheet has two custom callbacks. You can enable or disable either callback.


COMPONENT: faultanalyzer
EXAMPLENAME: ManualFaultTriggersExample
EXAMPLETITLE: Manual Fault Triggers Example
PRODUCT: MATLAB;Simulink Fault Analyzer;Simulink
DESCRIPTION:
Control manual triggers in a model. You can manually trigger faults during simulation by setting their trigger status.


COMPONENT: faultanalyzer
EXAMPLENAME: ReferencedModelWithFaultExample
EXAMPLETITLE: Example Referenced Model with a Fault
PRODUCT: MATLAB;Simulink Fault Analyzer;Simulink
DESCRIPTION:
How a referenced model that contains a fault interacts with a top model. The reference model also contains a fault that only appears in this instance of the model. To view the parent model, open the mdlref_basic_1 model.


COMPONENT: faultanalyzer
EXAMPLENAME: SystemComposerModelWithFaultExample
EXAMPLETITLE: Example System Composer Model with Fault
PRODUCT: MATLAB;Simulink Fault Analyzer;System Composer;Simulink
DESCRIPTION:
Model faults in a System Composer model. The model contains three Simulink model references, and one of the connections has a fault.


COMPONENT: faultanalyzer
EXAMPLENAME: MultipleReferencedModelsWithAFaultExample
EXAMPLETITLE: Example with Multiple Instances of a Referenced Model with a Fault
PRODUCT: MATLAB;Simulink Fault Analyzer;Simulink
DESCRIPTION:
How a model with multiple instances of a model reference stores faults. To view the parent model, open the mdlref_basic_2 model.


COMPONENT: fixedpoint
EXAMPLENAME: DataTypeOptimizationWithCustomMetricsExample
EXAMPLETITLE: Perform Data Type Optimization with Custom Behavioral Constraints
PRODUCT: MATLAB;Fixed-Point Designer;DSP System Toolbox
DESCRIPTION:
Use Model Verification blocks to specify custom behavioral constraints for data type optimization with fxpopt .


COMPONENT: fixedpoint
EXAMPLENAME: ComplexBurstSolveQlessQRForgettingFactorExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Complex Burst Matrix Solve Using Q-less QR Decomposition with Forgetting Factor

DESCRIPTION:
Use the hardware-efficient Complex Burst Matrix Solve Using Q-less QR Decomposition with Forgetting Factor block.


COMPONENT: fixedpoint
EXAMPLENAME: GenerateCodeForHalfPrecisionSystemsExample
EXAMPLETITLE: Generate Code for Half Precision Systems
PRODUCT: MATLAB;Embedded Coder;Simulink;Fixed-Point Designer
DESCRIPTION:
You can generate C code targeting .ert targets for Simulink models using the half-precision data type. Code generation for .ert targets requires an Embedded Coder® license.


COMPONENT: fixedpoint
EXAMPLENAME: SpecifySignalTolerancesExample
EXAMPLETITLE: Specify Signal Tolerances
PRODUCT: Fixed-Point Designer;MATLAB;Simulink
DESCRIPTION:
Apply and remove tolerances from signals in a system. In this example, you add tolerances to a DataTypeWorkflow.proposalSettings object, and then remove all tolerances from this object.


COMPONENT: fixedpoint
EXAMPLENAME: CORDICSigmoidExample
EXAMPLETITLE: How to Use CORDIC Sigmoid HDL Optimized Block
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Demonstrates how to compute the sigmoid activation of a given real-valued set of data using the CORDIC Sigmoid HDL Optimized block.


COMPONENT: fixedpoint
EXAMPLENAME: ComplexBurstRegularizedQRMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Complex Burst Matrix Solve Using QR Decomposition with Tikhonov Regularization

DESCRIPTION:
Use the Complex Burst Matrix Solve Using QR Decomposition block to solve the regularized least-squares matrix equation


COMPONENT: fixedpoint
EXAMPLENAME: SquareJacobiSVDFIFOExample
EXAMPLETITLE: Implement HDL Optimized SVD with Backpressure Signal and HDL FIFO Block
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Implement hardware-efficient singular value decomposition (SVD) using the Square Jacobi SVD HDL Optimized block with backpressure control and an HDL FIFO block.


COMPONENT: fixedpoint
EXAMPLENAME: NormalizedReciprocalExample
EXAMPLETITLE: How to Use HDL Optimized Normalized Reciprocal
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
How and when to use the normalizedReciprocal function and the Normalized Reciprocal HDL Optimized block to compute the normalized reciprocal of an input.


COMPONENT: fixedpoint
EXAMPLENAME: ComplexPartialSystolicRegularizedQlessQRMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
EXAMPLETITLE:
Implement Hardware-Efficient Complex Partial-Systolic Matrix Solve Using Q-less QR Decomposition with Tikhonov Regularization

DESCRIPTION:
Use the Complex Partial-Systolic Matrix Solve Using QR Decomposition block to solve the regularized least-squares matrix equation


COMPONENT: fixedpoint
EXAMPLENAME: ComplexBurstQlessQRForgettingFactorExample
EXAMPLETITLE: Implement Hardware-Efficient Complex Burst Q-less QR with Forgetting Factor
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Use the hardware-efficient Complex Burst Q-less QR Decomposition with Forgetting Factor Whole R Output block.


COMPONENT: fixedpoint
EXAMPLENAME: RealBurstSolveQlessQRForgettingFactorExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Real Burst Matrix Solve Using Q-less QR Decomposition with Forgetting Factor

DESCRIPTION:
Use the hardware-efficient Real Burst Matrix Solve Using Q-less QR Decomposition with Forgetting Factor block.


COMPONENT: fixedpoint
EXAMPLENAME: ComplexPartialSystolicSolveQlessQRForgettingFactorExample
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
EXAMPLETITLE:
Implement Hardware-Efficient Complex Partial-Systolic Matrix Solve Using Q-less QR Decomposition with Forgetting Factor

DESCRIPTION:
How to use the Complex Partial-Systolic Matrix Solve Using Q-less QR Decomposition with Forgetting Factor block.


COMPONENT: fixedpoint
EXAMPLENAME: OptimizeAnExistingLookupTableExample
EXAMPLETITLE: Optimize an Existing Lookup Table
PRODUCT: Fixed-Point Designer;MATLAB;Simulink
DESCRIPTION:
Optimize an existing Lookup Table block for memory efficiency. Open the model containing the Lookup Table block that you want to optimize.


COMPONENT: fixedpoint
EXAMPLENAME: ComplexPartialSystolicRegularizedQRMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Complex Partial-Systolic Matrix Solve Using QR Decomposition with Tikhonov Regularization

DESCRIPTION:
Use the Complex Partial-Systolic Matrix Solve Using QR Decomposition block to solve the regularized least-squares matrix equation


COMPONENT: fixedpoint
EXAMPLENAME: RealPartialSystolicMatrixSolveQlessQRForgettingFactorExample
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
EXAMPLETITLE:
Implement Hardware-Efficient Real Partial-Systolic Matrix Solve Using Q-less QR Decomposition with Forgetting Factor

DESCRIPTION:
How to use the Real Partial-Systolic Matrix Solve Using Q-less QR Decomposition with Forgetting Factor block.


COMPONENT: fixedpoint
EXAMPLENAME: FixedPointToFixedPointInheritedConversionExample
EXAMPLETITLE: Fixed-Point to Fixed-Point Inherited Conversion
PRODUCT: MATLAB;Simulink;Fixed-Point Designer
DESCRIPTION:
Use the Data Type Conversion block FixPt To FixPt Inherited . Because Simulink® propagates data types throughout a block diagram, fixed-point utility modeling can be templatized for multiple use scenarios. The data type inheritance capability can be given additional information through the use of various relative-type specifications. The FixPt To FixPt Inherited block provides a way to specify that "this signal should have the same fixed-point data type as that signal" by wiring it up to the signals of interest.


COMPONENT: fixedpoint
EXAMPLENAME: SpecifyFixedPointMathPropertiesInAMATLABFunctionBlockExample
EXAMPLETITLE: Specify Fixed-Point Math Properties in MATLAB Function Block
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Specify fixed-point math properties in a MATLAB Function block. You can specify fimath properties to add fixed-point numbers without bit growth. The same methods also apply to subtraction and multiplication.


COMPONENT: fixedpoint
EXAMPLENAME: SquareJacobiSVDFeedforwardExample
EXAMPLETITLE: Implement HDL Optimized SVD in Feedforward Fashion Without Backpressure
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Implement a hardware-efficient singular value decomposition (SVD) using the Square Jacobi SVD HDL Optimized block in a feedforward fashion without backpressure.


COMPONENT: fixedpoint
EXAMPLENAME: RangeCollectionInTheFixedPointToolExample
EXAMPLETITLE: Range Collection in the Fixed-Point Tool
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Use the Range Collection workflow in the Fixed-Point Tool . The model used in this example is a simple FIR filter modeled using fixed-point data types. In this example, you analyze the numerical behavior of the model to determine the source of overflow in the Embedded Efficient Filter subsystem.


COMPONENT: fixedpoint
EXAMPLENAME: ConvertNeuralNetworkToFixedPointAndGenerateHDLCodeExample
EXAMPLETITLE: Convert Neural Network Algorithms to Fixed-Point Using fxpopt and Generate HDL Code
PRODUCT: MATLAB;Fixed-Point Designer;Deep Learning Toolbox;HDL Coder
DESCRIPTION:
Convert a neural network to fixed point using fixed-point optimization and lookup table optimization.


COMPONENT: fixedpoint
EXAMPLENAME: FixedPointFunctionApproximationExample
EXAMPLETITLE: Fixed-Point Function Approximation
PRODUCT: MATLAB;Simulink;Fixed-Point Designer
DESCRIPTION:
When a fixed-point library function is not available, fixed-point applications require an approximation of the function. Often, an interpolated look up table is used to store an approximation of the function over a specified range.


COMPONENT: fixedpoint
EXAMPLENAME: FixedPointToolExample
EXAMPLETITLE: Use the Fixed-Point Tool to Rescale a Fixed-Point Model
PRODUCT: MATLAB;Simulink;Fixed-Point Designer
DESCRIPTION:
Show you how to use the Fixed-Point Tool to refine the scaling of fixed-point data types associated with the feedback controller model fxpdemo_feedback. The Fixed-Point Tool enables multiple workflows for converting a model to use fixed-point data types.


COMPONENT: fixedpoint
EXAMPLENAME: HighPrecisionCalculationsInInterpolationBlockExample
EXAMPLETITLE: High Precision Calculations in Interpolation Block
PRODUCT: MATLAB;Fixed-Point Designer;Simulink;Simulink Coder
DESCRIPTION:
Perform high precision calculations in the Interpolation Using Prelookup block using internal rules. The Interpolation block allows the data type for intermediate results to be set.


COMPONENT: fixedpoint
EXAMPLENAME: HowDataTypeProposalsAreDeterminedForBusObjectsExample
EXAMPLETITLE: How Data Type Proposals Are Determined for Bus Objects
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
How the software determines the data types for elements of bus objects using the ex_bus_range model.


COMPONENT: fixedpoint
EXAMPLENAME: RealBurstRegularizedQRMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Real Burst Matrix Solve Using QR Decomposition with Tikhonov Regularization

DESCRIPTION:
Use the Real Burst Matrix Solve Using QR Decomposition block to solve the regularized least-squares matrix equation


COMPONENT: fixedpoint
EXAMPLENAME: ReplaceUnsupportedBlocksWithALookupTableApproximationExample
EXAMPLETITLE: Replace Unsupported Blocks with a Lookup Table Approximation
PRODUCT: Fixed-Point Designer;MATLAB;Simulink
DESCRIPTION:
In this example, you replace a block that is not supported for fixed-point conversion, with a lookup table approximation.


COMPONENT: fixedpoint
EXAMPLENAME: CORDICRotationAboutArbitraryAxisExample
EXAMPLETITLE: Hardware-Efficient Rotation About Arbitrary Axis Using CORDIC
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Implement rotation about an arbitrary axis using the CORDIC algorithm in Simulink®. The resulting model supports HDL code generation for deployment to FPGA or ASIC devices.


COMPONENT: fixedpoint
EXAMPLENAME: DoubleToFixedPointConversionExample
EXAMPLETITLE: Double to Fixed-Point Conversion
PRODUCT: MATLAB;Simulink;Fixed-Point Designer
DESCRIPTION:
How to convert signals between built-in and fixed-point data types and illustrates how fixed-point data types affect the representable precision and range. The fixed-point data type used in this model is fixdt(1,5,2) , which is a signed 5-bit number with 2 bits to the right of the binary point:


COMPONENT: fixedpoint
EXAMPLENAME: RealPartialSystolicRegularizedQRMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Real Partial-Systolic Matrix Solve Using QR Decomposition with Tikhonov Regularization

DESCRIPTION:
Use the Real Partial-Systolic Matrix Solve Using QR Decomposition block to solve the regularized least-squares matrix equation


COMPONENT: fixedpoint
EXAMPLENAME: ComplexPartialSystolicQRDiagonalLoadingMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
EXAMPLETITLE:
Implement Hardware-Efficient Complex Partial-Systolic Matrix Solve Using QR Decomposition with Diagonal Loading

DESCRIPTION:
How to use the Complex Partial-Systolic Matrix Solve Using QR Decomposition Block with diagonal loading.


COMPONENT: fixedpoint
EXAMPLENAME: RealPartialSystolicRegularizedQlessQRMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Real Partial-Systolic Matrix Solve Using Q-less QR Decomposition with Tikhonov Regularization

DESCRIPTION:
Use the Real Partial-Systolic Matrix Solve Using Q-less QR Decomposition block to solve the regularized least-squares matrix equation


COMPONENT: fixedpoint
EXAMPLENAME: NonSquareJacobiSVDExample
EXAMPLETITLE: How to Use Non-Square Jacobi SVD HDL Optimized Block
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Use the Non-Square Jacobi SVD HDL Optimized block to compute the singular value decomposition (SVD) of non-square matrices.


COMPONENT: fixedpoint
EXAMPLENAME: OptimizedFixedPointConversionInTheFixedPointToolExample
EXAMPLETITLE: Optimized Fixed-Point Conversion in the Fixed-Point Tool
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Use the Optimized Fixed-Point Conversion workflow in the Fixed-Point Tool . The model used in this example is a simple FIR filter modeled using floating-point data types. In this example, you specify known behavioral constraints for the output of the filter and optimize the fixed-point data types in the Embedded Efficient Filter subsystem.


COMPONENT: fixedpoint
EXAMPLENAME: DeriveRangesForSimulinkParameterObjectsExample
EXAMPLETITLE: Open the ex_derived_min_max_3 Model
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
The model displays the specified design minimum and maximum values for the Inport blocks. The design range for both Inport blocks is [1...2] .


COMPONENT: fixedpoint
EXAMPLENAME: RealBurstQlessQRForgettingFactorExample
EXAMPLETITLE: Implement Hardware-Efficient Real Burst Q-less QR with Forgetting Factor
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Use the hardware-efficient Real Burst Q-less QR Decomposition with Forgetting Factor Whole R Output block.


COMPONENT: fixedpoint
EXAMPLENAME: FixedPointOptimizationsUsingSpecifiedMinAndMaxValuesExample
EXAMPLETITLE: Fixed-Point Optimizations Using Specified Minimum and Maximum Values
PRODUCT: MATLAB;Simulink;Embedded Coder;Fixed-Point Designer
DESCRIPTION:
Optimize fixed-point operations in generated code using minimum and maximum values that you specify in a model. Minimum and maximum values can represent environmental limits or mechanical limits, such as the output ranges of sensors. The code generation software can use these values to create more efficient code by eliminating unreachable code branches and unnecessary utility functions.


COMPONENT: fixedpoint
EXAMPLENAME: FptMergeRangesExample
EXAMPLETITLE: Set up the Model
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Uses the ex_merge_ranges model. The model contains a sine wave input and two alternate noise sources, band-limited white noise and random uniform noise. In this example, define a Simulink.SimulationInput object and collect ranges using the Band-Limited White Noise source and the Random Number 1 source. Propose data types for the model based on the merged simulation ranges.


COMPONENT: fixedpoint
EXAMPLENAME: SquareJacobiSVDWithCovarianceMatExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Compute SVD of Non-Square Matrices Using Square Jacobi SVD HDL Optimized Block by Forming Covariance Matrices

DESCRIPTION:
Use the Square Jacobi SVD HDL Optimized block to compute the singular value decomposition (SVD) of non-square matrices by forming covariance matrices.


COMPONENT: fixedpoint
EXAMPLENAME: OpenHalfPrecisionModelExample
EXAMPLETITLE: Open Half-Precision Model
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Open the model for which you want to generate native half-precision C code. The model should use half-precision data types and be configured for code generation.


COMPONENT: fixedpoint
EXAMPLENAME: NonSquareJacobiSVDSimplifiedAXIExample
EXAMPLETITLE: Implement HDL Optimized SVD for Non-Square Matrix with Scalar Input and Simplified AXI4 Protocol
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Use the Non-Square Jacobi SVD HDL Optimized block to compute the singular value decomposition (SVD) of non-square matrices. The input data is in scalar format and uses simplified AXI4 protocol. The Non-Square Jacobi SVD HDL Optimized block uses the AMBA AXI handshake protocol for both input and output. The valid/ready handshake process is used to transfer data and control information. For more details about the handshake process, see Non-Square Jacobi SVD HDL Optimized. In certain use cases such as using this block with IP core generation workflow, this block needs to interface with upstream block using the Model Design for AXI4-Stream Interface Generation (HDL Coder). In this example, the sAXI2AXI block serves as an adapter between simplified AXI and AMBA AXI protocols. It also converts the scalar input into row format and feeds into the Non-Square Jacobi SVD HDL Optimized block.


COMPONENT: fixedpoint
EXAMPLENAME: OpenModelAndDefineSimulationScenariosExample
EXAMPLETITLE: Open Model and Define Simulation Scenarios
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Open the model. In this example, you optimize the data types of the Controller subsystem. The model is set up to use either a ramp input, or a random input.


COMPONENT: fixedpoint
EXAMPLENAME: SystolicQRSolverExample
EXAMPLETITLE: How to Use Systolic Matrix Solve Using QR Decomposition Block
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Use the Systolic Matrix Solve Using QR Decomposition block to compute the solution X of the least-squares matrix equation AX = B.


COMPONENT: fixedpoint
EXAMPLENAME: HandleOverflowsInSimulinkModelsExample
EXAMPLETITLE: Open the Model
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
This model contains a sine wave with an amplitude of 1.5 passed through two Data Type Conversion blocks. In the Data Type Conversion block, the Saturate on integer overflow parameter is selected. The Data Type Conversion1 block wraps when the signal is too large to fit into the output data type.


COMPONENT: fixedpoint
EXAMPLENAME: IterativeFixedPointConversionInTheFixedPointToolExample
EXAMPLETITLE: Iterative Fixed-Point Conversion in the Fixed-Point Tool
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Use the Iterative Fixed-Point Conversion workflow in the Fixed-Point Tool . The model used in this example is a simple FIR filter modeled using initial guesses for fixed-point data types. In this example, you specify known behavioral constraints for the output of the filter and improve the fixed-point data types in the Embedded Efficient Filter subsystem.


COMPONENT: fixedpoint
EXAMPLENAME: HowtoUseCORDICSquareRootHDLOptimizedExample
EXAMPLETITLE: How to Use CORDIC Square Root HDL Optimized Block
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Use the CORDIC Square Root HDL Optimized block to compute the square root of real non-negative scalars.


COMPONENT: fixedpoint
EXAMPLENAME: FixedPointDirectFormFilterExample
EXAMPLETITLE: Open the Fixed-Point Direct Form Filter Model
PRODUCT: MATLAB;Simulink;Fixed-Point Designer
DESCRIPTION:
Open the fxpdemo_direct_form2 model. This tutorial uses a fixed-point direct form filter implemented using fundamental building blocks such as Gain, Delay, and Sum. The model contains a Signal Generator block that supplies a square wave input to the filter.


COMPONENT: fixedpoint
EXAMPLENAME: FixedPointConversionAndDerivedRangeAnalysisExample
EXAMPLETITLE: Fixed-Point Conversion Using Fixed-Point Tool and Derived Range Analysis
PRODUCT: MATLAB;Fixed-Point Designer;Computer Vision Toolbox;DSP System Toolbox;Simulink
DESCRIPTION:
Use derived range analysis to collect ranges that then can be used by the Fixed-Point Tool to propose fixed-point scaling.


COMPONENT: fixedpoint
EXAMPLENAME: SquareJacobiSVDExample
EXAMPLETITLE: How to Use Square Jacobi SVD HDL Optimized Block
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Use the Square Jacobi SVD HDL Optimized block to compute the singular value decomposition (SVD) of square matrices.


COMPONENT: fixedpoint
EXAMPLENAME: RealBurstRegularizedQlessQRMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Real Burst Matrix Solve Using Q-less QR Decomposition with Tikhonov Regularization

DESCRIPTION:
Use the Real Burst Matrix Solve Using QR Decomposition block to solve the regularized least-squares matrix equation


COMPONENT: fixedpoint
EXAMPLENAME: ConvertSinglePrecisionLookupTableToHalfPrecisionExample
EXAMPLETITLE: Convert Single Precision Lookup Table to Half Precision
PRODUCT: MATLAB;Fixed-Point Designer;Simulink;Simulink Coder
DESCRIPTION:
Halve the memory size of a Lookup Table block while keeping the desired system performance by converting the lookup table to use half precision.


COMPONENT: fixedpoint
EXAMPLENAME: RealBurstAsyncQlessQRMatrixSolveExample
EXAMPLETITLE: Implement Hardware-Efficient Real Burst Asynchronous Matrix Solve Using Q-less QR Decomposition
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Implement a hardware-efficient solution to the real-valued matrix equation A'AX=B using the Real Burst Asynchronous Matrix Solve Using Q-less QR Decomposition block.


COMPONENT: fixedpoint
EXAMPLENAME: HardwareEfficientEulerRotationsUsingCORDICExample
EXAMPLETITLE: Hardware-Efficient Euler Rotations Using CORDIC
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
DESCRIPTION:
Implement Euler rotations using a CORDIC kernel. The resulting model is deployable to FPGA or ASIC devices.


COMPONENT: fixedpoint
EXAMPLENAME: ComplexBurstRegularizedQlessQRMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer
EXAMPLETITLE:
Implement Hardware-Efficient Complex Burst Matrix Solve Using Q-less QR Decomposition with Tikhonov Regularization

DESCRIPTION:
Use the Complex Burst Matrix Solve Using QR Decomposition block to solve the regularized least-squares matrix equation


COMPONENT: fixedpoint
EXAMPLENAME: HowHardwareImplementationSettingsAffectDataTypeProposalsExample
EXAMPLETITLE: Open the Model and Specify Hardware Implementation Settings
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
In the Configuration Parameters dialog box, on the Hardware Implementation pane, you can specify the Device vendor and Device type of your target hardware. The Fixed-Point Tool uses this information when it proposes fixed-point data types for objects in your model. For example, if you specify the target hardware to be an embedded processor, the tool will propose standard word lengths appropriate for the target.


COMPONENT: fixedpoint
EXAMPLENAME: RealPartialSystolicQRDiagonalLoadingMatrixSolveExample
PRODUCT: MATLAB;Fixed-Point Designer;Simulink
EXAMPLETITLE:
Implement Hardware-Efficient Real Partial-Systolic Matrix Solve Using QR Decomposition with Diagonal Loading

DESCRIPTION:
How to use the Real Partial-Systolic Matrix Solve Using QR Decomposition Block with diagonal loading.


COMPONENT: fixedpoint
EXAMPLENAME: ComplexBurstAsyncQlessQRMatrixSolveExample
EXAMPLETITLE: Implement Hardware-Efficient Complex Burst Asynchronous Matrix Solve Using Q-less QR Decomposition
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
Implement a hardware-efficient solution to the complex-valued matrix equation A'AX=B using the Complex Burst Asynchronous Matrix Solve Using Q-less QR Decomposition block.


COMPONENT: fixedpoint
EXAMPLENAME: ReplaceABlockWithAnApproximationExample
EXAMPLETITLE: Replace a Block with an Approximation
PRODUCT: Fixed-Point Designer;MATLAB;Simulink
DESCRIPTION:
Approximate a block using a lookup table approximation, replace the original block with the approximation, and then revert the block back to its original state.


COMPONENT: fixedpoint
EXAMPLENAME: ImportAnFxpOptimizationOptionsObjectIntoFixedPointToolExample
EXAMPLETITLE: Import an fxpOptimizationOptions Object into Fixed-Point Tool
PRODUCT: MATLAB;Fixed-Point Designer
DESCRIPTION:
You can import an fxpOptimizationOptions object into the Fixed-Point Tool to perform data type optimization in the app. By importing an fxpOptimizationOptions object rather than specifying settings manually in the app, you can easily save and restore your settings.


COMPONENT: fusion
EXAMPLENAME: TrackCloselySpacedTargetsUnderAmbiguityInSimulinkExample
EXAMPLETITLE: Track Closely Spaced Targets Under Ambiguity in Simulink
PRODUCT: MATLAB;Sensor Fusion and Tracking Toolbox;Simulink
DESCRIPTION:
Track objects in Simulink® with Sensor Fusion and Tracking Toolbox™ when the association of sensor detections to tracks is ambiguous. It closely follows the Tracking Closely Spaced Targets Under Ambiguity MATLAB® example.


COMPONENT: fusion
EXAMPLENAME: TrackPointTargetsInDenseClutterInSimulinkExample
EXAMPLETITLE: Track Point Targets in Dense Clutter Using GM-PHD Tracker in Simulink
PRODUCT: MATLAB;Sensor Fusion and Tracking Toolbox;Simulink
DESCRIPTION:
Radars generally receive echoes from all surfaces in the signal path. These unwanted back-scattered signals or echoes generated from physical objects are called clutter. In a densely cluttered environment, missed detections and false alarms make tracking objects a challenging task for conventional trackers such as Global Nearest-Neighbor (GNN) tracker. In such an environment a PHD tracker provides better estimation of objects as it can handle multiple detections per object per sensor without clustering them first. This example shows you how to track points targets in dense clutter using a Gaussian mixture probability hypothesis density (GM-PHD) tracker with a constant velocity model in Simulink. The example closely follows the Track Point Targets in Dense Clutter Using GM-PHD Tracker MATLAB® example.


COMPONENT: fusion
EXAMPLENAME: DefineAndTestTrackingArchitecturesInSimulinkExample
EXAMPLETITLE: Define and Test Tracking Architectures for System-of-Systems in Simulink
PRODUCT: MATLAB;Sensor Fusion and Tracking Toolbox;Simulink
DESCRIPTION:
Define architectures for a tracking system-of-systems in MATLAB and export them to a Simulink model. You compare various tracking system designs that includes multiple detection-level multi-object trackers and track fusers in Simulink. You use Simulink Variant systems to realize different architecture solutions for your system. This example closely follows the Define and Test Tracking Architectures for System-of-Systems MATLAB example.


COMPONENT: fusion
EXAMPLENAME: ExtendedObjectTrackingForMarineSurveillanceInSimulinkExample
EXAMPLETITLE: Extended Object Tracking with Radar for Marine Surveillance in Simulink
PRODUCT: MATLAB;Sensor Fusion and Tracking Toolbox;Simulink
DESCRIPTION:
Model a marine scenario, simulate detections from a marine surveillance radar, and configure a multi-target probability hypothesis density (PHD) tracker to estimate the location and size of simulated ships using the radar detections in Simulink®. Simulink provides a powerful environment for the modeling and simulation of dynamic systems and processes. This example closely follows the Extended Object Tracking with Radar for Marine Surveillance MATLAB® example.


COMPONENT: fusion
EXAMPLENAME: AirTrafficControlInSimulinkExample
EXAMPLETITLE: Air Traffic Control in Simulink
PRODUCT: MATLAB;Sensor Fusion and Tracking Toolbox;Simulink
DESCRIPTION:
Create a tracking system for an air traffic control center using a global nearest neighbor (GNN) tracker in Simulink.


COMPONENT: fuzzy
EXAMPLENAME: GenerateStructuredTextForFuzzySystemUsingPLCCoderExample
EXAMPLETITLE: Generate Structured Text for Fuzzy System Using Simulink PLC Coder
PRODUCT: Fuzzy Logic Toolbox;MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
You can generate Structured Text for a fuzzy inference system implemented in Simulink using a Fuzzy Logic Controller block.


COMPONENT: fuzzy
EXAMPLENAME: FieldOrientedControlOfPMSMUsingFISLearningExample
EXAMPLETITLE: FieldOrientedControlOfPMSMUsingFISLearningExample
PRODUCT:
MATLAB;Fuzzy Logic Toolbox;Global Optimization Toolbox;Simulink;Simulink Coder;Motor Control Blockset


COMPONENT: fuzzy
EXAMPLENAME: SimulateFISExample
EXAMPLETITLE: Simulate FIS
PRODUCT: Fuzzy Logic Toolbox;Simulink
DESCRIPTION:
The simulateTipper model computes tip values for specified food and service ratings using the Fuzzy Logic Controller block, which is configured to use the FIS stored in the tipper.fis file. For more information on how to create this FIS, see Build Fuzzy Systems Using Fuzzy Logic Designer.


COMPONENT: fuzzy
EXAMPLENAME: FuzzyPIDControlWithType2FISExample
EXAMPLETITLE: Fuzzy PID Control with Type-2 FIS
PRODUCT: MATLAB;Fuzzy Logic Toolbox;Control System Toolbox;Simulink
DESCRIPTION:
Create a type-2 fuzzy logic PID controller and compare its performance with a type-1 fuzzy PID controller and a conventional PID controller.


COMPONENT: fuzzy
EXAMPLENAME: AccessIntermediateOutputsOfFISTreeExample
EXAMPLETITLE: Access Intermediate Outputs of FIS Tree
PRODUCT: Fuzzy Logic Toolbox;Simulink
DESCRIPTION:
When you simulate a FIS tree, you can configure the fistree object to output the intermediate inference results from its component FIS objects.


COMPONENT: fuzzy
EXAMPLENAME: GenerateCodeForFuzzySystemUsingSimulinkCoderExample
EXAMPLETITLE: Generate Code for Fuzzy System Using Simulink Coder
PRODUCT: Fuzzy Logic Toolbox;MATLAB;Simulink;Simulink Coder
DESCRIPTION:
You can generate code for a fuzzy inference system implemented in Simulink using a Fuzzy Logic Controller block.


COMPONENT: fuzzy
EXAMPLENAME: SimulateFISTreeExample
EXAMPLETITLE: Simulate FIS Tree
PRODUCT: Fuzzy Logic Toolbox;Simulink
DESCRIPTION:
The simulateWeightedTipper model computes weighted tip values for specified food and service ratings using the FIS Tree block, which is configured to use the FIS tree stored in the weightedTipper.mat file. For more information on how to create this FIS tree, see Build FIS Tree Using Fuzzy Logic Designer.


COMPONENT: fuzzy
EXAMPLENAME: fuzzypiddemo
EXAMPLETITLE: Implement Fuzzy PID Controller in Simulink Using Lookup Table
PRODUCT: Control System Toolbox;Fuzzy Logic Toolbox;Simulink
DESCRIPTION:
Implement a fuzzy PID controller using a lookup table, and compare the controller performance with a traditional PID controller.


COMPONENT: fuzzy
EXAMPLENAME: SimulateFuzzyInferenceSystemExample
EXAMPLETITLE: Simulate Fuzzy Inference System
PRODUCT: Fuzzy Logic Toolbox;MATLAB;Simulink
DESCRIPTION:
Once you have implemented a fuzzy inference system using Fuzzy Logic Designer , using Neuro-Fuzzy Designer , or at the command line, you can simulate the system in Simulink.


COMPONENT: gpucoder
EXAMPLENAME: FogRectificationWithSimulinkExample
EXAMPLETITLE: GPU Code Generation for a Fog Rectification Simulink Model
PRODUCT:
MATLAB;GPU Coder;Image Processing Toolbox;Simulink;Computer Vision Toolbox;Embedded Coder;Parallel Computing Toolbox;MATLAB Coder;Simulink Coder

DESCRIPTION:
A typical implementation of fog rectification algorithm. The example uses conv2 , im2gray , and imhist (Image Processing Toolbox) functions. This example closely follows Fog Rectification example. This example illustrates the following concepts: Verification of GPU Environment.


COMPONENT: gpucoder
EXAMPLENAME: GenerateCUDACodeForSobelEdgeDetectionExample
EXAMPLETITLE: Generate CUDA Code For Sobel Edge Detection
PRODUCT: MATLAB;GPU Coder;MATLAB Coder;Simulink Coder;Simulink
DESCRIPTION:
Generate CUDA® code for a Sobel edge detection model. The edge detection model uses MATLAB Function blocks to implement the detection algorithm.


COMPONENT: gpucoder
EXAMPLENAME: AccelerateSobelEdgeDetectionExample
EXAMPLETITLE: Accelerate Sobel Edge Detection
PRODUCT: MATLAB;GPU Coder;MATLAB Coder;Simulink;Simulink Coder;Computer Vision Toolbox
DESCRIPTION:
Perform GPU-accelerated simulation of a Sobel edge detection model. The edge detection model uses MATLAB Function blocks to implement the detection algorithm.


COMPONENT: gpucoder
EXAMPLENAME: LaneDetectionUsingHoughlinesSimulinkExample
EXAMPLETITLE: GPU Code Generation for Lane Detection in Simulink
PRODUCT: MATLAB;GPU Coder;Image Processing Toolbox;Simulink;Embedded Coder;Computer Vision Toolbox
DESCRIPTION:
Generate CUDA® code for a Simulink® model that can detect and output lane marker boundaries on an image. This example takes RGB image as an input and uses the imresize , rgb2gray , ordfilt2 (Image Processing Toolbox), hough (Image Processing Toolbox), houghpeaks (Image Processing Toolbox), and houghlines (Image Processing Toolbox) functions that are part of Image Processing Toolbox™ to detect lane markings. This example closely follows Lane Detection on the GPU by Using the houghlines Function.


COMPONENT: hdlcoder
EXAMPLENAME: AbsorbDelaysToAvoidTimingDifferenceExample
EXAMPLETITLE: Use Delay Absorption While Modeling with Latency
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Model with latency to absorb design delays and prevent a timing mismatch between the original and generated model.


COMPONENT: hdlcoder
EXAMPLENAME: ClockRatePipeliningExample
EXAMPLETITLE: Increase Clock Frequency Using Clock-Rate Pipelining
PRODUCT: HDL Coder;Simulink;MATLAB
DESCRIPTION:
Apply clock-rate pipelining to optimize slow paths in your design and thereby reduce latency, increase clock frequency and decrease area usage. For more information on how to use clock-rate pipelining, see Clock-Rate Pipelining.


COMPONENT: hdlcoder
EXAMPLENAME: IPCoreGenerationOfI2CControllerToConfigureAudioCodecExample
EXAMPLETITLE: IP Core Generation of an I2C Controller IP to Configure the Audio Codec Chip
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Illustrates how to model an I2C controller using an I2C Master controller modeled using Stateflow® blocks for configuring the audio codec chip.


COMPONENT: hdlcoder
EXAMPLENAME: FPGAFloatingPointLibraryIPMappingExample
EXAMPLETITLE: FPGA Floating-Point Library IP Mapping
PRODUCT: MATLAB;Simulink;HDL Coder
DESCRIPTION:
Use vendor-specific floating-point IP libraries, such as Altera® and Xilinx®, to generate target specific HDL code. For more information on how to map designs to floating-point libraries, see Generate HDL Code for Vendor-Specific FPGA Floating-Point Target Libraries.


COMPONENT: hdlcoder
EXAMPLENAME: SingleRateResourceSharingArchitectureExample
EXAMPLETITLE: Single-Rate Resource Sharing Architecture
PRODUCT: MATLAB;Simulink;HDL Coder
DESCRIPTION:
How HDL Coder™ generates a single-rate architecture from a model to manage the execution of operations in the context of clock-rate pipelining and resource sharing. When you apply resource sharing to blocks in your design, HDL Coder decides the architecture to use based on the sample rate of the regions where sharing occurs. If resource sharing occurs in a region of the design that operates at the fastest base sample rate, then HDL Coder synthesizes a local multi-rate architecture, as described in Resource Sharing for Area Optimization. In this example, the shared resources are in a region that operates at a slower sample rate, so HDL Coder applies clock-rate pipelining and synthesizes a single-rate architecture.


COMPONENT: hdlcoder
EXAMPLENAME: SaveAndAccessHDLParametersInStructureExample
EXAMPLETITLE: Save and Access Non-Default HDL Parameters in a Structure Array
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Save non-default HDL model and block parameters in a structure array and access individual parameters.


COMPONENT: hdlcoder
EXAMPLENAME: GettingStartedWithTargetingIntelSoCDevicesExample
EXAMPLETITLE: Getting Started with Targeting Intel SoC Devices
PRODUCT: MATLAB;Simulink Coder;Embedded Coder;HDL Coder
DESCRIPTION:
Use the Simulink Toolstrip and Simulink Interface along with the hardware-software co-design workflow to blink LEDs at various frequencies on the Arrow® SoCKit® evaluation kit.


COMPONENT: hdlcoder
EXAMPLENAME: MapBusDatatypesToAXI4SlaveInterfacesExample
EXAMPLETITLE: Map Bus Data Types to AXI4 Slave Interfaces
PRODUCT: MATLAB;HDL Coder;HDL Verifier
DESCRIPTION:
Map bus data types to an AXI4 slave interface, generate an HDL IP core with a AXI4 Master interface, perform matrix multiplication in an HDL IP core, and write the output result to DDR memory. In this example, you:


COMPONENT: hdlcoder
EXAMPLENAME: AuthoringAReferenceDesignForAudioSystemOnAZYBOBoardExample
EXAMPLETITLE: Authoring a Reference Design for Audio System on a ZYBO Board
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Build a reference design to run an audio algorithm and access audio input and output on ZYBO™ Z7-10 board.


COMPONENT: hdlcoder
EXAMPLENAME: GettingStartedWithIntelQuartusProBasedDevicesExample
EXAMPLETITLE: Getting Started with Targeting Intel Quartus Pro Based Devices
PRODUCT: MATLAB;Simulink Coder;Embedded Coder
DESCRIPTION:
Define and register the board and reference design for the Intel® Arria10 SoC development kit. In this example, you use a partitioned hardware-software co-design implementation to blink LEDs at various frequencies. In this example, you register the Arria 10 SoC development kit and the reference design in the HDL Workflow Advisor. The reference design also shows the *Early I/O (Split bitstream)* feature supported by Intel Arria 10 SoC in HDL Workflow Advisor. This example uses Embedded Coder(R) to generate C code that runs on the ARM(R) processor to control the LED blink frequency. You can prepare your design for hardware and software implementation on the Intel Arria 10 SoC by deciding which system elements are performed by the programmable logic, and which system elements will run on the ARM Cortex-A9.


COMPONENT: hdlcoder
EXAMPLENAME: DeployModelWithAXI4StreamVideoInterfaceInZynqWorkflowExample
EXAMPLETITLE: Deploy Model with AXI4-Stream Video Interface on Zynq Hardware
PRODUCT: MATLAB;Simulink Coder;Embedded Coder;Computer Vision Toolbox;Vision HDL Toolbox
DESCRIPTION:
Use the AXI4-Stream Video interface to enable high speed video streaming on the generated HDL IP core.


COMPONENT: hdlcoder
EXAMPLENAME: DefineCustomBoardAndReferenceDesignForMicrochipWorkflowExample
EXAMPLETITLE: Define Custom Board and Reference Design for Microchip Workflow
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Define and register a custom board and reference design for a blinking LED model in the Microchip workflow of the HDL Workflow Advisor. You use a SmartFusion2® board, but you can define and register a custom board or a custom reference design for other Microchip platforms.


COMPONENT: hdlcoder
EXAMPLENAME: TargetingMicrochipPolarFireSoCIcicleKitExample
EXAMPLETITLE: Integrate HDL IP Core with Microchip PolarFire SoC Icicle Kit Reference Design
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Use the hardware-software co-design workflow to blink LEDs at various frequencies on the Microchip PolarFire® SoC Icicle kit.


COMPONENT: hdlcoder
EXAMPLENAME: IntegrateCustomHDLCodeUsingDocBlockExample
EXAMPLETITLE: Include Custom HDL Code Using Doc Block
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
The hdlcoderIncludeCustomHdlUsingDocBlockExample model shows how to integrate custom VHDL and Verilog code into your design with the DocBlock block.


COMPONENT: hdlcoder
EXAMPLENAME: ModelTriggerSignalAsClockInTriggeredSubsystemExample
EXAMPLETITLE: Model Trigger Signal As Clock in Triggered Subsystem
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Model trigger port of the Triggered Subsystem as a clock signal. Using trigger as clock functionality in the Triggered Subsystem enables you to use trigger signal as a clock in your generated HDL code.


COMPONENT: hdlcoder
EXAMPLENAME: GenerateReusableCodeForAtomicSubsystemsExample
EXAMPLETITLE: Generate Reusable Code for Atomic Subsystems
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
HDL code generation of a model that has identical atomic subsystems. If your design contains identical atomic subsystems, the coder generates one HDL module or entity for the subsystem and instantiates it multiple times.


COMPONENT: hdlcoder
EXAMPLENAME: DescriptionMultiRateIssueHDLExample
EXAMPLETITLE: Description
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
This issue occurs when your Simulink® model has a significantly large difference in sample rates or uses certain block implementations or optimizations that result in different clock-rate paths, such as:


COMPONENT: hdlcoder
EXAMPLENAME: GenerateBoardIndependentHDLIPCoreForMicrochipPlatformsExample
EXAMPLETITLE: Generate Board-Independent HDL IP Core for Microchip Platforms
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Generate an HDL IP core for generic Microchip platform. You generate an HDL IP core for an LED blinking model, then integrate this HDL IP core into a target Microchip platform of your choice. You can generate a board-independent custom IP core to use in an embedded system integration environment, such as Microchip Libero SoC tool.


COMPONENT: hdlcoder
EXAMPLENAME: GettingStartedWithZynqUltraScaleMPSoCPlatformExample
EXAMPLETITLE: Getting Started with Targeting Zynq UltraScale+ MPSoC Platform
PRODUCT: MATLAB;Simulink Coder;Embedded Coder
DESCRIPTION:
Use the hardware-software co-design workflow to blink LEDs at various frequencies on the Xilinx® Zynq® UltraScale+ MPSoC.


COMPONENT: hdlcoder
EXAMPLENAME: MapScalarPortsToAXI4MasterInterfacesExample
EXAMPLETITLE: Modeling for AXI4 Master Interfaces
PRODUCT: DSP System Toolbox;HDL Verifier;HDL Coder;MATLAB;Simulink
DESCRIPTION:
You can model your algorithm with Data and AXI4 Master protocol signals at the DUT ports and then map the signals to AXI4 Master interfaces.


COMPONENT: hdlcoder
EXAMPLENAME: DebugIPCoreUsingFPGADataCaptureExample
EXAMPLETITLE: Debug IP Core Using FPGA Data Capture
PRODUCT: MATLAB;HDL Verifier;DSP System Toolbox;Simulink;HDL Coder
DESCRIPTION:
Debug an IP core you generate in HDL Coder™ using only FPGA Data Capture as well as both AXI Manager and FPGA Data Capture together.


COMPONENT: hdlcoder
EXAMPLENAME: RAMMappingWithMATLABFunctionBlockExample
EXAMPLETITLE: RAM Mapping with the MATLAB Function Block
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
How to use RAM mapping optimization with MapPersistentVarsToRAM parameter for MATLAB Function blocks in your model.


COMPONENT: hdlcoder
EXAMPLENAME: DebugTestPointSignalsWithHDLCoderExample
EXAMPLETITLE: Model and Debug Test Point Signals with HDL Coder
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
An example that shows how to add test points to signals in your model and debug these signals in the generated HDL code.


COMPONENT: hdlcoder
EXAMPLENAME: GettingStartedWithTargetingXilinxZynqPlatformExample
EXAMPLETITLE: Getting Started with Targeting Xilinx Zynq Platform
PRODUCT: MATLAB;Simulink Coder;Embedded Coder;HDL Coder
DESCRIPTION:
Use the hardware-software co-design workflow to blink LEDs at various frequencies on the Xilinx® Zynq® ZC702 evaluation kit.


COMPONENT: hdlcoder
EXAMPLENAME: AuthoringReferenceDesignForAudioSystemOnIntelBoardExample
EXAMPLETITLE: Authoring a Reference Design for Audio System on Intel Board
PRODUCT: MATLAB;Simulink;HDL Coder
DESCRIPTION:
Build a reference design to run an audio algorithm and access audio input and output on an Intel® Arrrow® SoC board.


COMPONENT: hdlcoder
EXAMPLENAME: GenerateRecordTypesForArrayOfBusExample
EXAMPLETITLE: Generate Record Types for Array of Bus
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Model that has array of bus signal at the design under test (DUT) interface. Using Preserve Bus structure in the generated HDL code configuration option, you can generate code with array of record types for the array of bus signals.


COMPONENT: hdlcoder
EXAMPLENAME: PerformMatrixOperationUsingExternalMemoryExample
EXAMPLETITLE: Perform Matrix Operation Using External Memory
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Generate an HDL IP core with AXI4 Master interface, perform matrix multiplication in HDL IP core, and write output result to DDR memory.


COMPONENT: hdlcoder
EXAMPLENAME: DelayBalancingAndValidationModelExample
EXAMPLETITLE: Delay Balancing and Validation Model Workflow in HDL Coder
PRODUCT: Simulink;HDL Coder
DESCRIPTION:
How HDL Coder™ can automatically balance delays within a model. HDL Coder may introduce additional delays in the HDL implementation for a given model. These delays may be introduced by either certain block implementations or by optimizations for the purpose of improving the efficiency of the hardware implementations. However, introducing delays on only certain paths can result functional behavior that is different from the original intent of the user model, thereby violating functional equivalence between the original user model and the HDL implementation.


COMPONENT: hdlcoder
EXAMPLENAME: FrameToSampleConversionExample
EXAMPLETITLE: Generate HDL Code from a Frame-Based Model Example
PRODUCT: MATLAB;HDL Coder;Simulink;Computer Vision Toolbox
DESCRIPTION:
The Simulink model hdlFrame_Blur_2D_MLFB models a common image-processing frame-based blurring algorithm which uses a neighborhood processing pattern.


COMPONENT: hdlcoder
EXAMPLENAME: FieldOrientedControlOfAPermanentMagnetSynchronousMachineExample
EXAMPLETITLE: Field-Oriented Control of a Permanent Magnet Synchronous Machine
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Generate HDL code for a Field-Oriented Control (FOC) algorithm for a Permanent Magnet Synchronous Machine (PMSM).


COMPONENT: hdlcoder
EXAMPLENAME: DeployFrameBasedModelWithAXIStreamExample
EXAMPLETITLE: Deploy a Frame-Based Model with AXI4-Stream Interfaces
PRODUCT: MATLAB;HDL Coder;Simulink;Computer Vision Toolbox
DESCRIPTION:
Leverage the frame to sample optimization from HDL Coder™ to generate a sample-based IP core with AXI4-Stream interfaces from a frame-based Simulink® model. The generated IP core can then be deployed to hardware and verified using live streaming data from MATLAB®.


COMPONENT: hdlcoder
EXAMPLENAME: DynamicallyCreateReferenceDesignWithMasterOrSlaveOnlyExample
EXAMPLETITLE: Dynamically Create Reference Design with Master Only or Slave Only AXI4-Stream Interface
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Illustrates how to customize the reference design dynamically by using a callback function based on the reference design parameter options. Also, this example shows how you can customize the number of AXI4-Stream interface channels in your reference design to be Only AXI4-Stream Master interface, Only AXI4-Stream Slave interface or both the interfaces.


COMPONENT: hdlcoder
EXAMPLENAME: AuthoringAReferenceDesignForAudioSystemOnAZynqBoardExample
EXAMPLETITLE: Authoring a Reference Design for Audio System on a Zynq Board
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Build a reference design to run an audio algorithm and access audio input and output on a Zynq® board.


COMPONENT: hdlcoder
EXAMPLENAME: MultipleClocksAndResetsUsingTriggeredAndResettableExample
EXAMPLETITLE: Generate Multiple Clocks and Resets Using Triggered and Resettable Subsystems
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Model multiple clock and reset signals using triggered and resettable subsystems. Using trigger as clock functionality, you can model multiple clock signals from multiple triggered subsystems. By placing the resettable subsystem inside each triggered subsystem, you can model multiple reset signals in your Simulink model.


COMPONENT: hdlcoder
EXAMPLENAME: ImproveResourceSharingWithCloneDetectionExample
EXAMPLETITLE: Improve Resource Sharing with Clone Detection and Replacement
PRODUCT: HDL Coder;Simulink;Simulink Check
DESCRIPTION:
Automatically identify and replace recurring patterns by using the Clone Detector App. Consequently, it also improves opportunities for optimizing the model by using resource sharing. The Clone Detector App refactors models by identifying clones in a design and replacing clones with links to subsystem blocks in a library. This example uses a model that has already been modified for optimal resource sharing by using the Clone Detector App. To learn more about these modifications, see "Improve Resource Sharing with Design Modifications."


COMPONENT: hdlcoder
EXAMPLENAME: HDLVerifierCosimulationModelGenerationInHDLCoderExample
EXAMPLETITLE: HDL Verifier Cosimulation Model Generation in HDL Coder
PRODUCT: MATLAB;Simulink;HDL Coder;HDL Verifier
DESCRIPTION:
Reuse an existing Simulink® model to verify HDL Coder™ generated hardware designs using an HDL Verifier™ cosimulation test bench.


COMPONENT: hdlcoder
EXAMPLENAME: SimpleUpCounterModelHDLCoderExample
EXAMPLETITLE: Simple Counter Model
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Open this model to see a simple counter. The model counts up from zero to a threshold value and then wraps back to zero. The threshold value is set to 15 . To change the threshold value, change the value of the input to the count_threshold port. The Enable signal specifies whether the counter counts upward or holds the previous value. A value of 1 indicates that the counter counts upward continuously.


COMPONENT: hdlcoder
EXAMPLENAME: DefineCustomBoardAndReferenceDesignForMicrochipPureFPGAExample
EXAMPLETITLE: Define Custom Board and Reference Design for Microchip Pure FPGA Platforms
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Define and register a Pure FPGA boards and reference design for a LED blinking model in the IP Core Generation workflow of the HDL Workflow Advisor. You use a Microchip PolarFire® board, but you can define and register a custom board or a custom reference design for other Microchip platforms.


COMPONENT: hdlcoder
EXAMPLENAME: ModelIDSignalsToReduceMultipleAXI4MasterInterfacesExample
EXAMPLETITLE: Model ID Signals to Reduce the Number of AXI-4 Master Interfaces
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
You can model ID signals for the Simplified AXI4 Master Protocol in the IP core generation workflow. Use ID signals to:


COMPONENT: hdlcoder
EXAMPLENAME: SimulationMismatchWhenPipeliningWithFeedbackLoopsExample
EXAMPLETITLE: Resolve Simulation Mismatch When Pipelining with a Feedback Loop Outside the DUT
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Learn how to resolve simulation mismatch issues when using pipeline optimizations with feedback loops.


COMPONENT: hdlcoder
EXAMPLENAME: GenerateCodeForSubsystemsWithTunableMaskParametersExample
EXAMPLETITLE: Generate Reusable Code for Atomic Subsystems with Tunable Mask Parameters
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Using this example, you can generate HDL code for your design containing atomic subsystems that are identical except for their tunable mask parameter values. You can generate one HDL module or entity for the subsystem. In the generated code, the module or entity is instantiated multiple times.


COMPONENT: hdlcoder
EXAMPLENAME: ReduceTheRateDifferentialExample
EXAMPLETITLE: Recommendation 2: Reduce the Rate Differential
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
If you want to use a multirate model, it is recommended that you reduce the rate differential. Rate differential corresponds to the ratio of the fastest to the slowest clock rate in your design. If your target application requires two signal paths such that one signal path runs in time units of nanoseconds (ns) and the other signal path runs in time units of microseconds (us), you can choose to retain the multirate paths in your model. Be aware that delay balancing can introduce a significantly large number of registers to balance the signal paths.


COMPONENT: hdlcoder
EXAMPLENAME: GenerateHDLCodeForTappedDelayEnabledResettableExample
EXAMPLETITLE: Simulate and Generate HDL Code for Tapped Delay Enabled Resettable Synchronous Block
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Implement the Tapped Delay Enabled Resettable Synchronous block in a Simulink® model that a delays scalar signal multiple sample periods and output all delayed versions when external Enable signal is true and external Reset signal is false. You also generate HDL code for the model.


COMPONENT: hdlcoder
EXAMPLENAME: IPCoreGenWorkflowWithAMicroBlazeProcessorKC705Example
EXAMPLETITLE: IP Core Generation Workflow with a MicroBlaze processor: Xilinx Kintex-7 KC705
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Use the HDL Coder™ IP Core Generation Workflow to develop reference designs for Xilinx® parts without an embedded ARM® processor present, but which still utilize the HDL Coder generated AXI interface to control the DUT. Specifically, this example will use the Xilinx Kintex-7 KC705 board and a MicroBlaze™ soft processor running a LightWeightIP (lwIP) based TCP/IP firmware server in the reference design to access the HDL Coder generated DUT registers from anywhere on the connected network. Further, this example will also highlight the difference between accessing data from a collection of registers implemented as multiple scalar ports and a collection of registers implemented as a single vector port.


COMPONENT: hdlcoder
EXAMPLENAME: ImplementBitsToWordBlockExample
EXAMPLETITLE: Convert Input Vector of Bits to Integer
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Use the Bits to Word block in a Simulink® Model that converts vector of bits to an unsigned integer. You also generate HDL code for the model.


COMPONENT: hdlcoder
EXAMPLENAME: GenerateHDLCodeForNonlinearSimscapeModelsPartitioningExample
EXAMPLETITLE: Generate HDL Code for Nonlinear Simscape Models by Using Partitioning Solver
PRODUCT: MATLAB;HDL Coder;Simscape Electrical;Simscape;Simulink
DESCRIPTION:
Generate HDL code for a nonlinear Simscape model by using the Partitioning solver and deploy it onto a Speedgoat FPGA I/O module.


COMPONENT: hdlcoder
EXAMPLENAME: HDLCoderConvertIntegerToVectorOfBitsExample
EXAMPLETITLE: Convert Integer to Vector of Bits
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Implement the Word to Bits block in a Simulink® Model that converts an integer to a vector of bits. You also generate HDL code for the model.


COMPONENT: hdlcoder
EXAMPLENAME: UseMulticyclePathConstraintsToMeetTimingForSlowPathsExample
EXAMPLETITLE: Use Multicycle Path Constraints to Meet Timing for Slow Paths
PRODUCT: MATLAB;Simulink;HDL Coder
DESCRIPTION:
Apply multicycle path constraints in your design to meet timing requirements. Using multicycle path constraints can save area and reduce synthesis run times. For more information, see Meet Timing Requirements Using Enable-Based Multicycle Path Constraints.


COMPONENT: hdlcoder
EXAMPLENAME: DelayBalancingOnMultiRateDesignExample
EXAMPLETITLE: Delay Balancing on Multirate Designs
PRODUCT: HDL Coder;Simulink
DESCRIPTION:
How an indiscrete usage of Simulate rates on a multirate design can generate an undesirable HDL code, and provides few recommendations for optimal code generation.


COMPONENT: hdlcoder
EXAMPLENAME: GettingStartedWithHDLWorkflowCLIExample
EXAMPLETITLE: Get Started with HDL Workflow Command-Line Interface
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Use the HDL Workflow Advisor to run HDL workflows from the command line and the Export to script option.


COMPONENT: hdlcoder
EXAMPLENAME: FrameBasedFogRectificationForHDLCodeGenExample
PRODUCT: MATLAB;HDL Coder;Simulink;Computer Vision Toolbox
EXAMPLETITLE:
Use Neighborhood, Reduction, and Iterator Patterns with a Frame-Based Model or Function for HDL Code Generation

DESCRIPTION:
Generate HDL code from a frame-based design that models neighborhood, reduction, and iterator patterns.


COMPONENT: hdlcoder
EXAMPLENAME: OptimizeAreaUsageForFrameBasedModelTallArrayInputExample
EXAMPLETITLE: Optimize Area Usage for Frame-Based Algorithms with Tall Array Inputs
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Generate area efficient HDL code from a frame-based algorithm that has input data with significantly more rows than columns.


COMPONENT: hdlcoder
EXAMPLENAME: RecommendedBlockSettingsOfMultiportSwitchExample
EXAMPLETITLE: Recommended Block Parameter Settings of Multiport Switch Block for Numeric and Enumerated Types
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Use recommended block settings for Multiport Switch with numeric and enumerated types for HDL code generation.


COMPONENT: hdlcoder
EXAMPLENAME: ImproveResourceSharingWithDesignModificationsExample
EXAMPLETITLE: Improve Resource Sharing with Design Modifications
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Improve opportunities for resource sharing to optimize your model design by making certain modifications to your design. Resource sharing is an HDL Coder optimization that improves area utilization in the design on the target FPGA device. The optimization identifies multiple functionally equivalent resources and replaces them with a single resource. For more information, see Resource Sharing.


COMPONENT: hdlcoder
EXAMPLENAME: MapVectorPortsToAXI4StreamInterfacesExample
EXAMPLETITLE: Map Vector Ports to AXI4-Stream Interfaces
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Map vector data types to AXI4-Stream interfaces and generate an IP core. This example uses the legacy frame-based modeling where you design your algorithm to operate on a stream of samples and map the data ports to a streaming interface.


COMPONENT: hdlcoder
EXAMPLENAME: GenerateMultipleClocksUsingTriggerAsClockExample
EXAMPLETITLE: Generate Multiple Clocks Using Trigger As Clock
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Model multiple clock signals using triggered subsystems. Using trigger as clock functionality in the triggered subsystem enables you to use trigger signal as a clock in your generated HDL code. You can model an asynchronous clock domain design in Simulink® by using multiple triggered subsystem and use trigger as a clock functionality to generate separate clock signal for each triggered subsystem.


COMPONENT: hdlcoder
EXAMPLENAME: GenerateRecordTypesForBusSignalsAtSubsystemInterfaceExample
EXAMPLETITLE: Generate Record Types for Bus Signals at Subsystem Interface
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Generate VHDL code with record types for a model that has bus signals at the design under test (DUT) interface. The Preserve Bus structure in the generated HDL code configuration option enables you to generate code with record types for the bus signals. Use the record type to simplify your VHDL code. The record type is especially useful for simplifying interfaces and maintaining a large number of signals at the entity level.


COMPONENT: hdlcoder
EXAMPLENAME: CORDICAlgorithmUsingTheMATLABFunctionBlockExample
EXAMPLETITLE: CORDIC Algorithm Using the MATLAB Function Block
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Use HDL Coder™ to check, generate and verify HDL for a fixed-point CORDIC model implementing sin and cos trigonometric functions using the MATLAB Function Block.


COMPONENT: hdlcoder
EXAMPLENAME: DistPipeInsertionMATLABFunctionBlocksExample
EXAMPLETITLE: Use Distributed Pipelining Optimization in Models with MATLAB Function Blocks
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
How to optimize HDL code for MATLAB Function blocks for speed by distributing design delays and generated pipeline stages.


COMPONENT: hdlcoder
EXAMPLENAME: ScalarizationOfVectorPortsInGeneratedVHDLCodeExample
EXAMPLETITLE: Scalarization of Vector Ports in Generated VHDL Code
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Flatten vector signals on entire model or at DUT level into a structure of scalar signals in generated VHDL or SystemVerilog code.


COMPONENT: hdlcoder
EXAMPLENAME: ModelClockAndResetSignalUsingTriggeredAndResettableExample
EXAMPLETITLE: Model Single Clock and Reset Signal Using Triggered and Resettable Subsystems
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Model clock and reset signal using Triggered and Resettable subsystems. You can use trigger as clock functionality to model trigger port from triggered subsystem as a clock and use resettable subsystem to model reset port.


COMPONENT: hdlcoder
EXAMPLENAME: GenerateHDLForMealyFiniteStateMachineExample
EXAMPLETITLE: Generate HDL for Mealy Finite State Machine
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Stateflow chart that models a Mealy state machine using MATLAB as the action language. You can also generate the HDL code for Stateflow using HDL Coder™.


COMPONENT: hdlcoder
EXAMPLENAME: DeployFrameModelWithAXI4StreamVideoInZynqHardwareExample
EXAMPLETITLE: Deploy Frame-Based Models with AXI4-Stream Video Interfaces in Zynq-Based Hardware
PRODUCT: MATLAB;HDL Coder;Simulink;Computer Vision Toolbox
DESCRIPTION:
You can use the HDL Coder™ frame-to-sample optimization to design and deploy frame-based algorithms that use AXI4-Stream Video interfaces to enable high-speed video streaming.


COMPONENT: hdlcoder
EXAMPLENAME: HILImplementationOfSimscapeModelOnSpeedgoatFPGAIOModulesExample
EXAMPLETITLE: Hardware-in-the-Loop Implementation of Simscape Model on Speedgoat FPGA I/O Modules
PRODUCT: MATLAB;Simscape Electrical;HDL Coder;Simulink
DESCRIPTION:
Synthesize and generate FPGA bitstream from a Simscape half-wave rectifier model and deploy it onto a Speedgoat FPGA I/O 334-325K target.


COMPONENT: hdlcoder
EXAMPLENAME: Recommendation1UseASingleRateModelExample
EXAMPLETITLE: Recommendation 1: Use a Single-Rate Model
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Most applications that you target the HDL code for might not require such a large rate differential. In that case, it is recommended that you use a single-rate model. In this example, you can change the sample rate of the Constant block inside the hdlcoder_multirate_high_differential subsystem to be the same as that of the base model.


COMPONENT: hdlcoder
EXAMPLENAME: HDLCoderServomotorControllerWithUARTForXilinxExample
EXAMPLETITLE: FPGA Servomotor Controller with UART interface for Xilinx Board
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Uses hdlcoderUARTServoControllerExampleXilinx model that is designed to work with a Xilinx Virtex-5 ML506 development board.


COMPONENT: hdlcoder
EXAMPLENAME: FPGASynthesisFromFrameBasedModelsExample
EXAMPLETITLE: Synthesize Code for Frame-Based Model
PRODUCT: MATLAB;HDL Coder;Simulink;Computer Vision Toolbox
DESCRIPTION:
Generate HDL code for a Sobel edge detection frame algorithm and calculate the frames per second of your design by synthesizing the generated code with the Simulink® HDL Workflow Advisor.


COMPONENT: hdlcoder
EXAMPLENAME: HardwareDesignPatternsUsingTheMATLABFunctionBlockExample
EXAMPLETITLE: Create Hardware Design Patterns Using the MATLAB Function Block For HDL Code Generation
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Use the HDL design patterns library em_hdl_design_patterns to implement patterns that use the MATLAB Function block to solve common hardware modeling problems.


COMPONENT: hdlcoder
EXAMPLENAME: NativeFloatingPointTargetConfigurationExample
EXAMPLETITLE: Create Floating-Point Configuration with Native Floating Point and Generate Code
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Create a floating-point target configuration with the native floating-point support in HDL Coder, and then generate code.


COMPONENT: hdlcoder
EXAMPLENAME: HdlcoderReadbackofAXI4RegistersExample
EXAMPLETITLE: Inspect the Written Values of AXI4 Slave Registers by Using the Readback Methods
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Describes the different techniques to read the AXI4 slave input registers in your design. It shows the process of how to enable readback on AXI4 slave input registers and read the values of AXI4 slave input registers for your design.


COMPONENT: hdlcoder
EXAMPLENAME: GettingStartedWithMixedDesignOfNFPandHFPExample
EXAMPLETITLE: Design Model by Using HDL Coder Native Floating Point and Intel Hard Floating Point
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Create a model design that uses both HDL Coder™ native floating-point (NFP) and Intel® hard floating-point (HFP) IP. Using the NFP and HFP blocks together in a mixed design offers better FPGA resource utilizations. For complex models, this mixed design allows you to have bigger design into the FPGA fabric.


COMPONENT: hdlcoder
EXAMPLENAME: UsingMATLABAsAXIMasterToControlIPCoreExample
EXAMPLETITLE: Use JTAG AXI Manager to Control HDL Coder Generated IP Core
PRODUCT: MATLAB;HDL Coder;HDL Verifier;Simulink
DESCRIPTION:
Specify automatic insertion of the HDL Verifier™ AXI Manager IP into a reference design. This example also explains how to use MATLAB® or Simulink® to configure the HDL Coder™ generated FPGA IP core.


COMPONENT: hdlcoder
EXAMPLENAME: AXI4StreamInterfaceInZynqWorkflowExample
EXAMPLETITLE: Deploy Model with AXI-Stream Interface in Zynq Workflow
PRODUCT: MATLAB;Simulink Coder;Embedded Coder;DSP System Toolbox
DESCRIPTION:
Use the AXI4-Stream interface to enable high speed data transfer between the processor and FPGA on Zynq hardware.


COMPONENT: hdlcoder
EXAMPLENAME: FloatingPointSupportFieldOrientedControlAlgorithmExample
EXAMPLETITLE: Floating Point Support: Field-Oriented Control Algorithm
PRODUCT: MATLAB;Simscape Electrical;HDL Coder;Simulink
DESCRIPTION:
In this example you review a Field-Oriented Control (FOC) algorithm for a Permanent Magnet Synchronous Machine (PMSM) implemented using single-precision and half-precision floating-point types.


COMPONENT: hdlcoder
EXAMPLENAME: HDLCoderServomotorControllerWithUARTForIntelExample
EXAMPLETITLE: FPGA Servomotor Controller with UART interface for Intel Board
PRODUCT: MATLAB;HDL Coder
DESCRIPTION:
Uses hdlcoderUARTServoControllerExampleAltera model that is designed to work with a Altera DE2-115 development and education board.


COMPONENT: hdlcoder
EXAMPLENAME: UsingForEachSubsystemsInHDLCoderExample
EXAMPLETITLE: Using ForEach Subsystems in HDL Coder
PRODUCT: MATLAB
DESCRIPTION:
Use a For Each Subsystem to implement a streaming square root algorithm by cascading identical CORDIC iterations. You can then generate code for the algorithm by using HDL Coder™.


COMPONENT: hdlv_spchdl
EXAMPLENAME: UseSystemVerilogDPIToVerify5GWirelessApplicationsExample
EXAMPLETITLE: Verify 5G Wireless Applications Using SystemVerilog DPI
DESCRIPTION: Use SystemVerilog DPI components to verify 5G wireless applications in an HDL environment.
PRODUCT:
MATLAB;Simulink;Wireless HDL Toolbox;HDL Coder;HDL Verifier;Fixed-Point Designer;MATLAB Coder;Simulink Coder;5G Toolbox


COMPONENT: hdlverifier
EXAMPLENAME: GenerateNativeSystemVerilogAssertionsFromSimulinkExample
EXAMPLETITLE: Generate Native SystemVerilog Assertions from Simulink
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Generate native SystemVerilog assertions from assertions in a Simulink® model. This capability is useful whenever you need the same assertion behavior in Simulink and in your HDL testing environment.


COMPONENT: hdlverifier
EXAMPLENAME: VideoProcessingAccelerationUsingFPGAintheLoopExample
EXAMPLETITLE: Validate and Accelerate Video Algorithm with Cosimulation and FPGA-in-the-Loop
PRODUCT: MATLAB;Simulink;Fixed-Point Designer;Computer Vision Toolbox;DSP System Toolbox;HDL Coder
DESCRIPTION:
Validate a video processing algorithm using cosimulation and accelerate this process using FPGA-in-the-loop (FIL). The process analyzes a simple system that sharpens an RGB video input at 24 frames per second (FPS). You enhance the RGB video feed using FIR filter. Then, to validate the design, you leverage simulator-based and hardware-based verification features provided with HDL Verifier™ toolbox.


COMPONENT: hdlverifier
EXAMPLENAME: AutoGeneratedMemoryMapWithIndividualAddressOptionExample
EXAMPLETITLE: Auto-Generated Memory Map with Individual Address Option
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Highlights the use of the auto-generated memory map with individual address option when you generate a SystemC™/TLM component from a Simulink® model using the tlmgenerator target for either Simulink Coder or Embedded Coder™.


COMPONENT: hdlverifier
EXAMPLENAME: RelatingHDLClocksAndResetsWithSimulinkSampleTimesExample
EXAMPLETITLE: Relating HDL Clocks and Resets with Simulink Sample Times
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Illustrates the relationship of Simulink® sample times to HDL clocks and resets. The example uses HDL Verifier™ to cosimulate a synchronous Verilog parity check module. The example also contains the following:


COMPONENT: hdlverifier
EXAMPLENAME: ManchesterReceiverAbsoluteTimeModeExample
EXAMPLETITLE: Manchester Receiver (Absolute Time Mode)
PRODUCT: MATLAB;HDL Verifier;Simulink;Communications Toolbox
DESCRIPTION:
Verification of a Manchester encoder using HDL Verifier with Simulink. Manchester encoding is a simple modulation scheme that converts baseband digital data to an encoded waveform with no DC component. The most widely known application of this technique is Ethernet.


COMPONENT: hdlverifier
EXAMPLENAME: IntegrateSystemVerilogDPIIntoUVMFrameworkWorkflowExample
EXAMPLETITLE: Integrate SystemVerilog DPI into UVM Framework Workflow
PRODUCT: MATLAB;HDL Verifier;Fixed-Point Designer
DESCRIPTION:
Generate reusable verification components from a Simulink® model as SystemVerilog DPI components using HDL Verifier™ software. You use the MATLAB-to-UVMF (mtlb2uvmf) workflow to create Universal Verification Methodology (UVM) test benches quickly. For more information on mtlb2uvmf workflow, see MathWorks Integration from Siemens Verification Academy.


COMPONENT: hdlverifier
EXAMPLENAME: VerifyTheCombinationOfHandWrittenAndGeneratedHDLCodeExample
EXAMPLETITLE: Verify the Combination of Hand-Written and Generated HDL Code
PRODUCT: MATLAB;Simulink;Fixed-Point Designer;HDL Coder;Communications Toolbox
DESCRIPTION:
Uses HDL cosimulation and FPGA-in-the-loop (FIL) simulation to verify an HDL design comprising generated and legacy HDL code. The term "legacy" is used here to indicate code that may have been hand-written, purchased from a third party or generated for another project and saved for reuse in this design.


COMPONENT: hdlverifier
EXAMPLENAME: AlgorithmVerificationWithAFILSourceBlockExample
EXAMPLETITLE: Algorithm Verification with a FIL Source Block
PRODUCT:
MATLAB;Simulink;Fixed-Point Designer;Computer Vision Toolbox;DSP System Toolbox;HDL Coder;Signal Processing Toolbox

DESCRIPTION:
Verify an HDL design quickly and efficiently using FPGA-in-the-Loop (FIL). The test bench is synthesized together with the Design Under Test (DUT), the result is downloaded to an FPGA board, and the test is run with FIL. Using FIL for this process enables high speed generation and processing of test stimulus, with results returned to Simulink® for analysis. This example executes these tasks for an image processing use case.


COMPONENT: hdlverifier
EXAMPLENAME: ImportedIPXACTWithMemoryMapExample
EXAMPLETITLE: Imported IP-XACT with Memory Map
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Use an imported IP-XACT specification with memory map when you generate a SystemC™ or a Transaction Level Modeling (TLM) component from a Simulink® model with the tlmgenerator target. You can use the tlmgenerator target for either Simulink Coder™ or Embedded Coder™.


COMPONENT: hdlverifier
EXAMPLENAME: UsingVerifyStatementWithTestSequenceBlockExample
EXAMPLETITLE: Generating Functional Coverage in SystemVerilog from Simulink Test verify Calls
PRODUCT: MATLAB;Simulink;Simulink Coder;Simulink Test;HDL Verifier
DESCRIPTION:
Demonstrates how to test a projector control system using model simulation, and how to generate a SystemVerilog DPI component for some of the controller's high level requirements that are specified in a Test Sequence block. This will allow the requirement verification used for model simulation to be reused in the HDL simulator with minimal effort.


COMPONENT: hdlverifier
EXAMPLENAME: GettingStartedWithSystemVerilogDPIComponentGenerationExample
EXAMPLETITLE: Get Started with SystemVerilog DPI Component Generation
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Generate a SystemVerilog DPI component from a proportional-integral-derivative (PID) controller in a Simulink® model and how to export the component to an HDL simulator.


COMPONENT: hdlverifier
EXAMPLENAME: ManchesterReceiverUsingCommunicationsToolboxExample
EXAMPLETITLE: Manchester Receiver Using Communications Toolbox
PRODUCT: MATLAB;HDL Verifier;Simulink;Communications Toolbox
DESCRIPTION:
Verification of a Manchester encoder. Manchester encoding is a simple modulation scheme that converts baseband digital data to an encoded waveform with no DC component. The most widely known application of this technique is Ethernet.


COMPONENT: hdlverifier
EXAMPLENAME: ComparingHDLAndSimulinkCodeCoverageUsingCosimulationExample
EXAMPLETITLE: Comparing HDL and Simulink Code Coverage Using Cosimulation
PRODUCT: MATLAB;Simulink;Fixed-Point Designer
DESCRIPTION:
Achieve complete code coverage of an HDL cruise controller design using Simulink® and an HDL Simulator.


COMPONENT: hdlverifier
EXAMPLENAME: UntimedSystemCTLMSimulationExample
EXAMPLETITLE: Untimed SystemC/TLM Simulation
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Highlights the use of the 'Untimed' timing mode when you generate a SystemC™/TLM component from a Simulink® model using the tlmgenerator target for either Simulink® Coder™ or Embedded Coder®.


COMPONENT: hdlverifier
EXAMPLENAME: GenerateUVMTestBenchWithDriverAndMonitorFromSimulinkExample
EXAMPLETITLE: Include Driver and Monitor in UVM Test Bench
PRODUCT: MATLAB;HDL Verifier;Simulink;Simulink Coder;Fixed-Point Designer
DESCRIPTION:
Uses the uvmbuild function to generate a Universal Verification Methodology (UVM) test bench, which includes a UVM driver and monitor from a Simulink® design and test bench.


COMPONENT: hdlverifier
EXAMPLENAME: TimescalesAbsoluteRelativeAndAutomaticExample
EXAMPLETITLE: Timescales: Absolute, Relative and Automatic
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Illustrates the various Timescale settings within the HDL Cosimulation block and explains how these affect the timing relationship of Simulink® and the HDL simulator. We use a simple Verilog parity check model to show the timing relationship of Simulink and the HDL simulator (ModelSim® or Xcelium™) used for cosimulation.


COMPONENT: hdlverifier
EXAMPLENAME: LooselyTimedSystemCTLMSimulationExample
EXAMPLETITLE: Loosely-Timed SystemC/TLM Simulation
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Highlights the use of the 'Timed' timing mode when you generate a SystemC™/TLM component from a Simulink® model using the tlmgenerator target for either Simulink® Coder™ or Embedded Coder®.


COMPONENT: hdlverifier
EXAMPLENAME: GenerateBitLogicVectorDataTypesExample
EXAMPLETITLE: Generate Bit Vector and Logic Vector Data Types
PRODUCT: MATLAB;Simulink;Simulink Coder;Fixed-Point Designer;HDL Verifier
DESCRIPTION:
Generate bit or logic vector data types in the SystemVerilog interface of the DPI component. This capability is useful whenever having an exact width of the port is important to integrate the DPI component in your testbench.


COMPONENT: hdlverifier
EXAMPLENAME: ImportedIPXACTWithoutMemoryMapExample
EXAMPLETITLE: Imported IP-XACT Without Memory Map
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Use an imported IP-XACT specification without memory map when you generate a SystemC™/TLM component from a Simulink® model with the tlmgenerator target. You can use the tlmgenerator target for either Simulink Coder or Embedded Coder™.


COMPONENT: hdlverifier
EXAMPLENAME: NoMemoryMapOptionExample
EXAMPLETITLE: No Memory Map Option
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Highlights the use of the no memory map option when you generate a SystemC™/TLM component from a Simulink® model using the tlmgenerator target for either Simulink Coder or Embedded Coder™.


COMPONENT: hdlverifier
EXAMPLENAME: ManchesterReceiverUsingMixedDesignVerilogAndVHDLExample
EXAMPLETITLE: Manchester Receiver Using Mixed Design (Verilog and VHDL)
PRODUCT: MATLAB;HDL Verifier;Communications Toolbox;Simulink
DESCRIPTION:
Verification of a Manchester encoder using mixed HDL languages, VHDL and Verilog. Manchester encoding is a simple modulation scheme which converts baseband digital data into an encoded waveform with no DC component. The most widely known application of this technique is Ethernet.


COMPONENT: hdlverifier
EXAMPLENAME: CosimulateVivadoFFTIPCoreWithSimulinkExample
EXAMPLETITLE: Cosimulate Vivado FFT IP Core with Simulink
PRODUCT: MATLAB;HDL Verifier;Simulink;DSP System Toolbox;Fixed-Point Designer;Signal Processing Toolbox
DESCRIPTION:
Using HDL Verifier™, you can set up cosimulation between Simulink® and an IP core from the Xilinx® Vivado® simulator. This setup allows you to design your Simulink algorithm to include a Xilinx IP implementation in the system and use Simulink as a test bench. To verify the IP core, you can use the specialized stimulus and visualization scopes from Simulink.


COMPONENT: hdlverifier
EXAMPLENAME: ManchesterReceiverUsingMultipleCosimulationBlocksExample
EXAMPLETITLE: Manchester Receiver Using Multiple Cosimulation Blocks
PRODUCT: MATLAB;HDL Verifier;Communications Toolbox;Simulink
DESCRIPTION:
Simulates a digital receiver of Manchester encoded data. Manchester encoding is a simple modulation scheme that converts baseband digital data to an encoded waveform with no DC component. The most widely known application of this technique is Ethernet.


COMPONENT: hdlverifier
EXAMPLENAME: GettingStartedWithTLMGeneratorExample
EXAMPLETITLE: Get Started with TLM Generator
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Configure a Simulink® model to generate a SystemC™/TLM component using the tlmgenerator target for either Simulink Coder™ or Embedded Coder®.


COMPONENT: hdlverifier
EXAMPLENAME: BatchModeCosimulationOfManchesterReceiverExample
EXAMPLETITLE: Batch Mode Cosimulation of Manchester Receiver
PRODUCT: MATLAB;HDL Verifier;Communications Toolbox;Simulink
DESCRIPTION:
Illustrates using MATLAB® to start HDL simulator in batch mode and performing cosimulation with Simulink® using the HDL Verifier™ HDL Cosimulation block.


COMPONENT: hdlverifier
EXAMPLENAME: VerifyDigitalUpConverterUsingFPGAintheLoopExample
EXAMPLETITLE: Verify Digital Up-Converter Using FPGA-in-the-Loop
PRODUCT: MATLAB;Simulink;Fixed-Point Designer;DSP System Toolbox;HDL Coder;Signal Processing Toolbox
DESCRIPTION:
Verify a digital up-converter design generated with Filter Design HDL Coder™ using FPGA-in-the-Loop simulation.


COMPONENT: hdlverifier
EXAMPLENAME: AccelCommSystemSimUsingFILExample
EXAMPLETITLE: Accelerate Communications System Simulation Using FPGA-in-the-Loop
PRODUCT: MATLAB;Simulink;Fixed-Point Designer;Communications Toolbox
DESCRIPTION:
Uses FPGA-in-the-loop (FIL) simulation to accelerate part of a communications system. The application uses the Viterbi algorithm to decode a convolutional encoded random stream that is BPSK modulated, sent through an AWGN channel, and then demodulated. Using a sample-by-sample approach leads to a modest speedup over normal Simulink® simulation, while using the "Process as Frames" option leads to further speedup.


COMPONENT: hdlverifier
EXAMPLENAME: FramebasedScramblerUsingCommunicationsToolboxTMExample
EXAMPLETITLE: Frame-based Scrambler Using Communications Toolbox
PRODUCT: MATLAB;HDL Verifier;Simulink;Communications Toolbox
DESCRIPTION:
Illustrates the validation of an HDL implementation of a 6-order scrambler. A scrambler is used in communication systems to randomize transitions in the transmitted signal by shuffling the bits. One purpose of scrambling is to reduce the length of strings of 0s or 1s in a transmitted signal, since a long string of 0s or 1s may cause transmission synchronization problems. Scrambling may also be used as a cheap encryption technique. This example consists of two models. The first model scrambler_frame validates the HDL implementation and the second model scrambler_fsk uses the HDL scrambler as part of a communication channel.


COMPONENT: hdlverifier
EXAMPLENAME: CosimCommandLineSimulinkExample
EXAMPLETITLE: Command-Line Workflow for Verifying Raised Cosine Filter in Simulink
PRODUCT: MATLAB;HDL Verifier
DESCRIPTION:
Cosimulate a raised cosine filter in Simulink® using the command-line interface. It follows the same workflow to generate cosimulation artifacts as in Get Started with Simulink HDL Cosimulation, but it uses the command line instead of the Cosimulation Wizard.


COMPONENT: hdlverifier
EXAMPLENAME: BuildingHDLTestBenchForQAMTransceiverModelExample
EXAMPLETITLE: Build HDL Test Bench for QAM Transceiver Model
PRODUCT:
MATLAB;Simulink;Simulink Coder;Fixed-Point Designer;Communications Toolbox;DSP HDL Toolbox;HDL Verifier

DESCRIPTION:
Build a behavioral test bench using SystemVerilog DPI-C component generation. This test bench is used for the verification of synthesizable HDL code of a 64-QAM transmitter and receiver.


COMPONENT: hdlverifier
EXAMPLENAME: FrameBasedCosimulationExampleExample
EXAMPLETITLE: Frame-Based Cosimulation Example
PRODUCT: MATLAB;HDL Verifier;Simulink
DESCRIPTION:
Use the HDL Cosimulation block to cosimulate a VHDL implementation of a simple lowpass filter. In the example, you compare the performance of the simulation using frame-based and sample-based signals.


COMPONENT: hdlverifier
EXAMPLENAME: AutoGeneratedMemoryMapWithSingleAddressOptionExample
EXAMPLETITLE: Auto-Generated Memory Map with Single Address Option
PRODUCT: MATLAB;Simulink;Simulink Coder;HDL Verifier
DESCRIPTION:
Highlights the use of the auto-generated memory map with single address option when you generate a SystemC™/TLM component from a Simulink® model using the tlmgenerator target for either Simulink Coder or Embedded Coder™.


COMPONENT: icomm
EXAMPLENAME: DataValueAndQualityOfOPCUANodesInSimulinkExample
EXAMPLETITLE: Monitor Data Value and Quality of OPC UA Nodes in Simulink
PRODUCT: MATLAB;Industrial Communication Toolbox;Simulink
DESCRIPTION:
Implement a dashboard showing instantaneous data value and quality of specific OPC Unified Architecture (UA) nodes using Simulink® blocks of the Industrial Communication Toolbox™.


COMPONENT: icomm
EXAMPLENAME: GetStartedOPCUASimulinkExample
EXAMPLETITLE: Get Started with OPC UA in Simulink
PRODUCT: MATLAB;Industrial Communication Toolbox;Simulink
DESCRIPTION:
Read and write data to nodes available on an OPC Unified Architecture (UA) server using Simulink® blocks of the Industrial Communication Toolbox™. You can connect to the server using a Simulink model which acts as an OPC UA client. You can perform read and write operations in the model using the OPC UA Read and OPC UA Write blocks.


COMPONENT: ident
EXAMPLENAME: OnlinePolynomialModelEstimationExample
EXAMPLETITLE: Online ARMAX Polynomial Model Estimation
PRODUCT: System Identification Toolbox;MATLAB;Simulink
DESCRIPTION:
Implement an online polynomial model estimator. You estimate two ARMAX models for a nonlinear chemical reaction process. These models capture the behavior of the process at two operating conditions. The model behavior is identified online and used to adjust the gains of an adaptive PI controller during system operation.


COMPONENT: ident
EXAMPLENAME: iddemosl
EXAMPLETITLE: Estimating Continuous-Time Models Using Simulink Data
PRODUCT: MATLAB;System Identification Toolbox;Simulink
DESCRIPTION:
Illustrates how models simulated in Simulink® can be identified using System Identification Toolbox™. The example describes how to deal with continuous-time systems and delays, as well as the importance of the intersample behavior of the input.


COMPONENT: ident
EXAMPLENAME: NonlinearARXModelOfSIEngineTorqueDynamicsExample
EXAMPLETITLE: Nonlinear ARX Model of SI Engine Torque Dynamics
PRODUCT: MATLAB;System Identification Toolbox;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Describes modeling the nonlinear torque dynamics of a spark-ignition (SI) engine as a nonlinear ARX model. The identified model can be used for hardware-in-the-loop (HIL) testing, powertrain control, diagnostic, and training algorithm design. For example, you can use the model for aftertreatment control and diagnostics algorithm development. For more information on nonlinear ARX models, see Nonlinear ARX Models.


COMPONENT: ident
EXAMPLENAME: SimulateIdentifiedLinearModelInSimulinkInitialConditionsExample
EXAMPLETITLE: Simulate Identified Linear Model in Simulink with Initial Conditions
PRODUCT: MATLAB;System Identification Toolbox;Simulink
DESCRIPTION:
Set the initial states for simulating a linear model such that the simulation provides a best fit to measured input-output data.


COMPONENT: ident
EXAMPLENAME: OnlineStateEstimationUsingLinearModelsExample
EXAMPLETITLE: Online State Estimation Using Identified Models - Linear Models
PRODUCT:
MATLAB;System Identification Toolbox;Signal Processing Toolbox;Control System Toolbox;Simulink;DSP System Toolbox

DESCRIPTION:
Generate the state-transition and measurement functions for online state and output estimation using linear identification techniques.


COMPONENT: ident
EXAMPLENAME: OnlineRLSExample
EXAMPLETITLE: Online Recursive Least Squares Estimation
PRODUCT: MATLAB;System Identification Toolbox;Simulink
DESCRIPTION:
Implement an online recursive least squares estimator. You estimate a nonlinear model of an internal combustion engine and use recursive least squares to detect changes in engine inertia.


COMPONENT: ident
EXAMPLENAME: NeuralStateSpaceModelOfSIEngineTorqueDynamicsExample
EXAMPLETITLE: Neural State-Space Model of SI Engine Torque Dynamics
PRODUCT: MATLAB;System Identification Toolbox;Simulink;Deep Learning Toolbox
DESCRIPTION:
Describes reduced order modeling (ROM) of the nonlinear torque dynamics of a spark-ignition (SI) engine using a neural state-space model. The identified model can be used for hardware-in-the-loop (HIL) testing, powertrain control, diagnostics, and training algorithm design. For example, you can use the model for after-treatment control and diagnostic algorithm development. For more information on neural state-space models, see Neural State-Space Models.


COMPONENT: ident
EXAMPLENAME: MatchOutputOfSimAndNonlinearARXBlockExample
EXAMPLETITLE: Match Output of sim Command and Nonlinear ARX Model Block
PRODUCT: MATLAB;System Identification Toolbox;Simulink
DESCRIPTION:
Reproduce command-line sim results for an estimated nonlinear system in Simulink. When you have an estimated system model, you can simulate it either with the command-line sim command or with Simulink. The two outputs do not match precisely unless you base both simulations on the same initial conditions. You can achieve this match by estimating the initial conditions in your MATLAB model and applying both in the sim command and in your Simulink model.


COMPONENT: ident
EXAMPLENAME: EstimateParametersOfSystemUsingSimulinkRLSEstimatorBlockExample
EXAMPLETITLE: Estimate Parameters of System Using Simulink Recursive Estimator Block
PRODUCT: MATLAB;System Identification Toolbox;Simulink
DESCRIPTION:
Use a model containing Simulink recursive estimator to accept input and output signals, construct a regressor signal, and estimate system parameters.


COMPONENT: ident
EXAMPLENAME: iddemo_Linearization
EXAMPLETITLE: Linear Approximation of Complex Systems by Identification
PRODUCT: MATLAB;System Identification Toolbox;Simulink
DESCRIPTION:
Obtain linear approximations of a complex, nonlinear system by means of linear model identification.


COMPONENT: ident
EXAMPLENAME: SurrogateModelingUsingGaussianProcessBasedNLARXModelsExample
EXAMPLETITLE: Surrogate Modeling Using Gaussian Process-Based NLARX Model
PRODUCT: MATLAB;System Identification Toolbox;Statistics and Machine Learning Toolbox;Simscape;Simulink
DESCRIPTION:
In this example, you replace a hydraulic cavitation cycle model in Simulink with a surrogate nonlinear ARX (NLARX) model to facilitate faster simulation.


COMPONENT: ident
EXAMPLENAME: MatchOutputOfCompareCommandAndNonlinearARXModelBlockExample
EXAMPLETITLE: Match Output of compare Command and Nonlinear ARX Model Block
PRODUCT: System Identification Toolbox;MATLAB;Simulink
DESCRIPTION:
In this example, you first use the compare command to match the simulated output of a nonlinear ARX model to measured data. You then reproduce the simulated output using a Nonlinear ARX Model block.


COMPONENT: ident
EXAMPLENAME: HammersteinWienerModelOfSIEngineTorqueDynamicsExample
EXAMPLETITLE: Hammerstein-Wiener Model of SI Engine Torque Dynamics
PRODUCT: MATLAB;System Identification Toolbox;Simulink
DESCRIPTION:
Describes modeling the nonlinear torque dynamics of a spark-ignition (SI) engine as a Hammerstein-Wiener model. The identified model can be used for hardware-in-the-loop (HIL) testing, powertrain control, diagnostic, and training algorithm design. For example, you can use the model for aftertreatment control and diagnostics algorithm development. For more information on Hammerstein-Wiener models, see Hammerstein-Wiener Models.


COMPONENT: ident
EXAMPLENAME: OnlineStateEstimationUsingNonlinearModelsExample
EXAMPLETITLE: Online State Estimation Using Identified Models - Nonlinear Models
PRODUCT:
MATLAB;System Identification Toolbox;Deep Learning Toolbox;Statistics and Machine Learning Toolbox;Signal Processing Toolbox;Simulink

DESCRIPTION:
Generate the state-transition and measurement functions for online state and output estimation using nonlinear system identification techniques.


COMPONENT: ident
EXAMPLENAME: ParameterAndStateEstimationUsingParticleFilterBlockExample
EXAMPLETITLE: Parameter and State Estimation in Simulink Using Particle Filter Block
PRODUCT: MATLAB;System Identification Toolbox;Simulink
DESCRIPTION:
Demonstrates the use of Particle Filter block in System Identification Toolbox™. A discrete-time transfer function parameter estimation problem is reformulated and recursively solved as a state estimation problem.


COMPONENT: ident
EXAMPLENAME: SimulateNonlinearARXModelInSimulinkExample
EXAMPLETITLE: Simulate Nonlinear ARX Model in Simulink
PRODUCT: System Identification Toolbox;MATLAB;Simulink
DESCRIPTION:
Compare the simulated output of a Nonlinear ARX Model block to the measured output of a system. You improve the agreement between the measured and simulated responses by estimating initial state values.


COMPONENT: ident
EXAMPLENAME: ReducedOrderModelingOfANonlinearMSDSystemUsingIdentExample
PRODUCT: MATLAB;System Identification Toolbox;Simulink Control Design;Control System Toolbox;Simulink
EXAMPLETITLE:
Reduced Order Modeling of a Nonlinear Dynamical System as an Identified Linear Parameter Varying Model

DESCRIPTION:
Identify a linear parameter varying reduced order model of a cascade of nonlinear mass-spring-damper systems.


COMPONENT: ident
EXAMPLENAME: SimulateHammersteinWienerModelInSimulinkRExample
EXAMPLETITLE: Simulate Hammerstein-Wiener Model in Simulink
PRODUCT: System Identification Toolbox;MATLAB;Simulink
DESCRIPTION:
Compare the simulated output of a Hammerstein-Wiener Model block to the measured output of a system. You improve the agreement between the measured and simulated responses by estimating initial state values.


COMPONENT: infineonaurix
EXAMPLENAME: GettingStartedWithInfineonAURIXTC4xMicrocontrollersExample
EXAMPLETITLE: Getting Started with Embedded Coder Support Package for Infineon AURIX TC4x Microcontrollers
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Use Embedded Coder® Support Package for Infineon® AURIX™ TC4x Microcontrollers to run a Simulink® model on Infineon AURIX TC4x board.


COMPONENT: infineonaurix
EXAMPLENAME: DataHandlingOfQSPIUsingInterruptsExample
EXAMPLETITLE: Data Handling of QSPI Using Interrupts
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
The handling of QSPI data of array size 12 using interrupts for Infineon AURIX™ TC4x Microcontroller.


COMPONENT: infineonaurix
EXAMPLENAME: CodeVerificationAndValidationWithPILExample
EXAMPLETITLE: Code Verification and Validation with PIL
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Use Embedded Coder® Support Package for Infineon AURIX™ TC4x Microcontrollers for code verification and validation using PIL.


COMPONENT: kerasimporter
EXAMPLENAME: ClassifySequenceOfImagesInSimulinkWithTensorFlowNetworkExample
EXAMPLETITLE: Classify Images in Simulink with Imported TensorFlow Network
PRODUCT: MATLAB;Deep Learning Toolbox;Simulink;Computer Vision Toolbox
DESCRIPTION:
Import a pretrained TensorFlow network using importTensorFlowNetwork , and then use the Predict block for image classification in Simulink .


COMPONENT: legomindstormsev3
EXAMPLENAME: DriveWithPIDControlExample
EXAMPLETITLE: Drive with PID Control
PRODUCT: MATLAB
DESCRIPTION:
Simulate a simple closed-loop control algorithm in Simulink® and how to run it on LEGO® MINDSTORMS® EV3 hardware.


COMPONENT: legomindstormsev3
EXAMPLENAME: CommunicatingWithLegomindstormsev3UsingXCPSimulationExample
EXAMPLETITLE: Communicating with LEGO MINDSTORMS EV3 Hardware Using XCP-Based Simulation
PRODUCT: MATLAB
DESCRIPTION:
Tune the parameters and monitor the signals of an algorithm running on the LEGO® MINDSTORMS® EV3 hardware using XCP-based simulation.


COMPONENT: legomindstormsev3
EXAMPLENAME: LineTrackingExample
EXAMPLETITLE: Implement Line Tracking Using LEGO MINDSTORMSEV3 Hardware
PRODUCT: MATLAB
DESCRIPTION:
Implement a line tracking algorithm for a two-wheeled robot built with LEGO® MINDSTORMS® EV3 hardware.


COMPONENT: legomindstormsev3
EXAMPLENAME: ControllingLEGOMINDSTORMSEV3RobotRaspPiSenseHATExample
EXAMPLETITLE: Controlling LEGO MINDSTORMS EV3 Robot Using Raspberry Pi Sense HAT
PRODUCT: MATLAB;Instrument Control Toolbox
DESCRIPTION:
Read the Accelerometer on Raspberry Pi® Sense HAT and use this data to control the movement of a LEGO® MINDSTORMS® EV3 robot.


COMPONENT: legomindstormsev3
EXAMPLENAME: ControllingLEGOMINDSTORMSEV3RobotFromHostComputerExample
EXAMPLETITLE: Control LEGO MINDSTORMS EV3 Robot from Host Computer
PRODUCT: MATLAB;Instrument Control Toolbox
DESCRIPTION:
Create a Simulink® model to communicate between the Host PC and the LEGO® MINDSTORMS® EV3 robot. The Simulink model running on the Host PC will exchange data with the EV3 brick and control the motion of the EV3 robot.


COMPONENT: legomindstormsev3
EXAMPLENAME: ObjectTrackingExample
EXAMPLETITLE: Track Colored Objects Using Pixy2 Vision Sensor
PRODUCT: MATLAB
DESCRIPTION:
Implement an object tracking system using a LEGO® MINDSTORMS® EV3 hardware and a Pixy2 vision sensor.


COMPONENT: legomindstormsev3
EXAMPLENAME: CommunicatingWithLEGORMINDSTORMSREV3TMHardwareExample
EXAMPLETITLE: Communicating with LEGO MINDSTORMS EV3 Hardware
PRODUCT: MATLAB
DESCRIPTION:
Tune the parameter values of and monitor the signals from an algorithm running on LEGO® MINDSTORMS® EV3 hardware.


COMPONENT: legomindstormsev3
EXAMPLENAME: GettingStartedWithLEGORMINDSTORMSREV3TMHardwareExample
EXAMPLETITLE: Getting Started with LEGO MINDSTORMS EV3 Hardware
PRODUCT: MATLAB
DESCRIPTION:
Use Simulink® Support Package for LEGO® MINDSTORMS® EV3 Hardware to run a Simulink model on LEGO MINDSTORMS EV3 hardware.


COMPONENT: legomindstormsev3
EXAMPLENAME: LEGOObjectTrackingSystemPixy2PIDControllerExample
EXAMPLETITLE: LEGO EV3 Object Tracking System Using Pixy2 Vision Sensor and PID Controller
PRODUCT: MATLAB
DESCRIPTION:
Improve the efficiency of an object tracking system using a Proportional Integral Derivative (PID) controller. The object tracking system has been built using the LEGO® MINDSTORMS® EV3 hardware and Pixy2 vision sensor.


COMPONENT: lidar
EXAMPLENAME: GenerateLidarPointCloudDataForDrivingScenarioExample
EXAMPLETITLE: Generate Lidar Point Cloud Data for Driving Scenario with Multiple Actors
PRODUCT: MATLAB;Lidar Toolbox;Simulink;Automated Driving Toolbox
DESCRIPTION:
Generate lidar point cloud data for a driving scene with roads, pedestrians, and vehicles created using a drivingScenario object.


COMPONENT: lidar
EXAMPLENAME: LidarSensorModelIntegrationWithRRAndCosimulationWithUEExample
EXAMPLETITLE: Integrate Lidar Sensor Model with RoadRunner Scenario and Cosimulate with Unreal Engine
PRODUCT: MATLAB;Lidar Toolbox;Automated Driving Toolbox;Simulink
DESCRIPTION:
Integrate lidar sensor model with RoadRunner Scenario using Simulink and cosimulate with Unreal Engine .


COMPONENT: lidar
EXAMPLENAME: MultiLidarCalibrationExample
EXAMPLETITLE: Multi-Lidar Calibration
PRODUCT: MATLAB;Lidar Toolbox;Simulink;Automated Driving Toolbox
DESCRIPTION:
Calibrate multiple 3-D lidar sensors mounted on a vehicle to estimate a relative transformation between them. Traditional methods, such as marker-based registration, are difficult when the lidar sensors have a negligible overlap between their fields of view (FOVs). The calibration also becomes more difficult as the number of lidar sensors increases. This example demonstrates the use of the trajectories of individual lidar sensors to estimate the transformation between them. This method of calibration is also known as hand-eye calibration.


COMPONENT: lte
EXAMPLENAME: PDSCHThroughputSimulinkExample
EXAMPLETITLE: PDSCH Throughput Performance in Simulink
PRODUCT: LTE Toolbox;MATLAB;Simulink
DESCRIPTION:
Demonstrates how to measure the physical downlink shared channel (PDSCH) throughput performance in Simulink® using LTE Toolbox™ for the following transmission modes (TM):


COMPONENT: lte
EXAMPLENAME: RFLTETransmitterExample
EXAMPLETITLE: Modeling and Testing an LTE RF Transmitter
PRODUCT: MATLAB;LTE Toolbox;RF Blockset;Simulink
DESCRIPTION:
Characterize the impact of radio frequency (RF) impairments, such as in-phase and quadrature (IQ) imbalance, phase noise, and power amplifier (PA) nonlinearities, on the performance of an LTE transmitter. The example generates the baseband LTE waveform, which consists of an E-UTRA test model (E-TM), by using LTE Toolbox™ software and models the RF transmitter by using RF Blockset™ software.


COMPONENT: mcb
EXAMPLENAME: CommutationOfSRMUsingSensorFeedbackExample
EXAMPLETITLE: Commutation of SRM Using Sensor Feedback
PRODUCT:
MATLAB;Motor Control Blockset;Embedded Coder;Fixed-Point Designer;Simscape Electrical;C2000 Microcontroller Blockset

DESCRIPTION:
Implements a commutation system to control the speed of a three-phase 12/8 switched reluctance motor (SRM).


COMPONENT: mcb
EXAMPLENAME: OperatingModeExample
EXAMPLETITLE: Tune Control Parameter Gains in Hardware and Validate Plant
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Embedded Coder;C2000 Microcontroller Blockset;Fixed-Point Designer

DESCRIPTION:
Uses field-oriented control (FOC) to run a three-phase permanent magnet synchronous motor (PMSM) in different modes of operation for plant validation. FOC algorithm implementation needs the real-time feedback of the rotor position. This example uses a quadrature encoder sensor to measure the rotor position. For details about FOC, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: EstimateInductionMotorParametersUsingRecommendedHardwareExample
EXAMPLETITLE: Estimate Induction Motor Parameters Using Recommended Hardware
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Embedded Coder;C2000 Microcontroller Blockset
DESCRIPTION:
Determines the parameters of a three-phase AC induction motor (ACIM) using the recommended Texas Instruments™ hardware. The example determines these parameters:


COMPONENT: mcb
EXAMPLENAME: RunFieldOrientedControlModelPredictiveControlExample
EXAMPLETITLE: Run Field Oriented Control of PMSM Using Model Predictive Control
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Model Predictive Control Toolbox;Embedded Coder;C2000 Microcontroller Blockset

DESCRIPTION:
Uses Model Predictive Control (MPC) to control the speed of a three-phase permanent magnet synchronous motor (PMSM). MPC is a control technique that tunes and optimizes the inputs to a control system to minimize the error in the predicted system output and achieve the reference control objective over a period of time. This technique involves solving the objective function and finding an optimal input sequence at every sample time ( ). After each time step, the current state of the plant is considered as the initial state and the above process is repeated.


COMPONENT: mcb
EXAMPLENAME: PMSMParameterEstimationUsingRecommendedHardwareExample
EXAMPLETITLE: Estimate PMSM Parameters Using Parameter Estimation Blocks
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Embedded Coder;C2000 Microcontroller Blockset;Stateflow
DESCRIPTION:
Uses the parameter estimation blocks provided by Motor Control Blockset™ to estimate these parameters of a permanent magnet synchronous motor (PMSM) with a quadrature encoder sensor:


COMPONENT: mcb
EXAMPLENAME: AcimFocSensorlessExample
EXAMPLETITLE: Sensorless Field-Oriented Control of Induction Motor
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Embedded Coder;C2000 Microcontroller Blockset;Fixed-Point Designer

DESCRIPTION:
Uses sensorless position estimation to implement the field-oriented control (FOC) technique to control the speed of a three-phase AC induction motor (ACIM). For details about FOC, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: SpeedControlOfSRMWithOnlineDwellAngleComputationExample
EXAMPLETITLE: Dwell Angle Computation for SRM Speed Control
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Simscape Electrical;Fixed-Point Designer;Embedded Coder;C2000 Microcontroller Blockset;Stateflow

DESCRIPTION:
Compute the dwell angle of a 12/8 switched reluctance motor (SRM) online (while the motor runs). The example then uses the computed dwell angle along with a delta controller to control the motor speed.


COMPONENT: mcb
EXAMPLENAME: GenerateMotorControlModelsForSelectedAlgoAndHardwareExample
EXAMPLETITLE: Generate Motor Control Models for Selected Algorithm and Hardware
PRODUCT: MATLAB;Motor Control Blockset;Simulink
DESCRIPTION:
Use Motor Control Blockset™ to generate a Simulink® model that is configured for a specific hardware and motor control technique.


COMPONENT: mcb
EXAMPLENAME: SensorlessFocFOSMOExample
EXAMPLETITLE: Sensorless Field-Oriented Control of PMSM
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Fixed-Point Designer;Embedded Coder;C2000 Microcontroller Blockset

DESCRIPTION:
Implements the field-oriented control (FOC) technique to control the speed of a three-phase permanent magnet synchronous motor (PMSM). For details about FOC, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: AcimFocQepExample
EXAMPLETITLE: Field-Oriented Control of Induction Motor Using Speed Sensor
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Embedded Coder;C2000 Microcontroller Blockset;Fixed-Point Designer

DESCRIPTION:
Implements the field-oriented control (FOC) technique to control the speed of a three-phase AC induction motor (ACIM). The FOC algorithm requires rotor speed feedback, which is obtained in this example by using a quadrature encoder sensor. For details about FOC, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: PMSMParameterEstimationUsingSpeedGoatHardwareExample
EXAMPLETITLE: Estimate PMSM Parameters Using Parameter Estimation Blocks on Real-Time Systems
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Simulink Real-Time;Stateflow
DESCRIPTION:
Uses the parameter estimation blocks provided by Motor Control Blockset™ to estimate these parameters of a permanent magnet synchronous motor (PMSM):


COMPONENT: mcb
EXAMPLENAME: ACIMParameterEstimationUsingRecommendedHardwareExample
EXAMPLETITLE: Estimate Induction Motor Parameters Using Parameter Estimation Blocks
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Embedded Coder;C2000 Microcontroller Blockset;Stateflow
DESCRIPTION:
Uses the parameter estimation blocks provided by Motor Control Blockset™ to estimate these parameters of an AC induction motor (ACIM):


COMPONENT: mcb
EXAMPLENAME: FieldOrientedControlOfPMSMUsingReinforcementLearningExample
EXAMPLETITLE: Field-Oriented Control of PMSM Using Reinforcement Learning
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Reinforcement Learning Toolbox
DESCRIPTION:
Use the control design method of reinforcement learning to implement field-oriented control (FOC) of a permanent magnet synchronous motor (PMSM). The example uses FOC principles. However, it uses the reinforcement learning (RL) agent instead of the PI controllers. For more details about FOC, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: FocAutoTunerRealTimeSystemsExample
EXAMPLETITLE: Tune PI Controllers Using Field Oriented Control Autotuner Block on Real-Time Systems
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Simulink Control Design;Simulink Real-Time
DESCRIPTION:
Compute the gain values of PI controllers within the speed and current controllers by using the Field Oriented Control Autotuner block.


COMPONENT: mcb
EXAMPLENAME: SIUnitsExample
EXAMPLETITLE: Field-Oriented Control of PMSM Using SI Units
DESCRIPTION:
Implements the Field-Oriented Control (FOC) technique to control the speed of a three-phase Permanent Magnet Synchronous Motor (PMSM). However, instead of the per-unit representation of quantities (for details about the per-unit system, see Per-Unit System), the FOC algorithm in this example uses the SI units of signals to perform the computations. These are the signals and their SI units:


COMPONENT: mcb
EXAMPLENAME: SixStepBLDCQepHallExample
EXAMPLETITLE: Six-Step Commutation of BLDC Motor Using Sensor Feedback
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Simscape Electrical;Embedded Coder;C2000 Microcontroller Blockset;Fixed-Point Designer

DESCRIPTION:
Use six-step commutation technique to control speed and direction of rotation of a three-phase BLDC motor.


COMPONENT: mcb
EXAMPLENAME: FocHallExample
EXAMPLETITLE: Field-Oriented Control of PMSM Using Hall Sensor
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Fixed-Point Designer;Embedded Coder;C2000 Microcontroller Blockset

DESCRIPTION:
Implements the field-oriented control (FOC) technique to control the speed of a three-phase permanent magnet synchronous motor (PMSM). The FOC algorithm requires rotor position feedback, which is obtained by a Hall sensor. For details about FOC, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: FrequencyResponseEstimationOfPMSMFocQepExample
EXAMPLETITLE: Frequency Response Estimation of PMSM Using Field-Oriented Control
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Simulink Control Design;Embedded Coder;C2000 Microcontroller Blockset;Stateflow

DESCRIPTION:
Performs frequency response estimation (FRE) of a plant model running a three-phase permanent magnet synchronous motor (PMSM). When you simulate or run the model on the target hardware, the model runs tests to estimate the frequency response as seen by each PI controller (also known as raw FRE data) and plots the FRE data to provide a graphical representation of the plant model dynamics.


COMPONENT: mcb
EXAMPLENAME: FOCAutotunerExample
EXAMPLETITLE: Tune PI Controllers Using Field Oriented Control Autotuner
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Simulink Control Design;Embedded Coder;C2000 Microcontroller Blockset;Stateflow

DESCRIPTION:
Computes the gain values of PI controllers available in the speed and current control loops by using the Field Oriented Control Autotuner block. For details about this block, see Field Oriented Control Autotuner. For details about field-oriented control, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: DeterminePowerLossesTHDForPWMModulationMethodsExample
EXAMPLETITLE: Determine Power Losses and THD for PWM Methods
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Simscape Electrical
DESCRIPTION:
Calculates the inverter power loss and total harmonic distortion (THD) in motor current for different pulse-width modulation (PWM) methods. The example uses field-oriented control (FOC) algorithm that runs a permanent-magnet synchronous motor (PMSM) in speed control mode as a reference. The example only supports simulation.


COMPONENT: mcb
EXAMPLENAME: FieldWeakeningControlWithMTPAExample
EXAMPLETITLE: Field-Weakening Control (with MTPA) of PMSM
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Fixed-Point Designer;Embedded Coder;C2000 Microcontroller Blockset

DESCRIPTION:
Implements the field-oriented control (FOC) technique to control the torque and speed of a three-phase permanent magnet synchronous motor (PMSM). The FOC algorithm requires rotor position feedback, which is obtained by a quadrature encoder sensor. For details about FOC, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: EstimatePMSMParametersUsingTexasInstrumentsHardwareExample
EXAMPLETITLE: Estimate PMSM Parameters Using Recommended Hardware
DESCRIPTION:
Determines the parameters of a permanent magnet synchronous motor (PMSM) using the recommended Texas Instruments™ hardware. The tool determines these parameters:


COMPONENT: mcb
EXAMPLENAME: CodeVerificationAndProfilingUsingPILTestingExample
EXAMPLETITLE: Code Verification and Profiling Using PIL Testing
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Embedded Coder;C2000 Microcontroller Blockset
DESCRIPTION:
Explains PIL profiling on Texas Instruments™ LAUNCHXL-F28379D hardware board. In processor-in-the-loop (PIL) simulation, the control algorithm executes in the target hardware, but the plant model runs on the host machine. The plant model simulates the input and output signals for the controller and communicates with the controller by using the serial communication interface. This functionality allows you to use PIL simulation to determine the execution time on the target hardware, which you can then compare with the execution time for simulating the model on the host machine.


COMPONENT: mcb
EXAMPLENAME: FOCQepExample
EXAMPLETITLE: Field-Oriented Control of PMSM Using Quadrature Encoder
DESCRIPTION:
Implements the field-oriented control (FOC) technique to control the speed of a three-phase permanent magnet synchronous motor (PMSM). The FOC algorithm requires rotor position feedback, which is obtained by a quadrature encoder sensor. For details about FOC, see Field-Oriented Control (FOC).


COMPONENT: mcb
EXAMPLENAME: SimscapeElectricalExample
EXAMPLETITLE: Model Switching Dynamics in Inverter Using Simscape Electrical
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Simscape Electrical;Embedded Coder;C2000 Microcontroller Blockset;Fixed-Point Designer

DESCRIPTION:
Uses field-oriented control (FOC) to control the speed of a three-phase permanent magnet synchronous motor (PMSM). It gives you the option to use these Simscape Electrical blocks as an alternative to the Average Value Inverter block in Motor Control Blockset™:


COMPONENT: mcb
EXAMPLENAME: MonitoringResolverExample
EXAMPLETITLE: Monitor Resolver Using Serial Communication
PRODUCT:
MATLAB;Simulink;Motor Control Blockset;Embedded Coder;Fixed-Point Designer;C2000 Microcontroller Blockset

DESCRIPTION:
Use the resolver sensor to measure the rotor position. The resolver consists of two stator (secondary) windings placed orthogonally around the resolver rotor (primary) winding. After you mount the resolver sensor over a PMSM, the resolver rotor winding rotates with the shaft of the running motor. Meanwhile, the controller provides a fixed-frequency excitation signal (alternating sinusoidal or square pulse) to the primary winding.


COMPONENT: mcb
EXAMPLENAME: FWCWithMTPAOfNonLinearPMSMUsingLUTExample
EXAMPLETITLE: Field-Weakening Control (with MTPA) of Nonlinear PMSM Using Lookup Table
PRODUCT: MATLAB;Motor Control Blockset;Simscape Electrical;Simulink
DESCRIPTION:
Uses a lookup table (LUT) for a nonlinear permanent magnet synchronous motor (PMSM) and controller to run the motor using field-weakening control (with maximum torque per ampere (MTPA)). Use this example to replicate and run a finite element analysis (FEA) based nonlinear, high-fidelity PMSM in simulation. This example helps motor design engineers to simulate high-performance motors in real-world motor control applications. In addition, control system engineers can use this example to design control algorithms for a given set of motor parameter data to achieve high levels of accuracy in tracking and controlling speed and torque as well as to meet efficiency requirements, especially for high-performance motors.


COMPONENT: mcb
EXAMPLENAME: QuadratureEncoderOffsetExample
EXAMPLETITLE: Quadrature Encoder Offset Calibration for PMSM
DESCRIPTION:
Calculates the offset between the d -axis of the rotor and encoder index pulse position as detected by the quadrature encoder sensor. The control algorithm (available in the field-oriented control and parameter estimation examples) uses this offset value to compute an accurate and precise position of the d -axis of rotor. The controller needs this position to implement the field-oriented control (FOC) correctly in the rotor flux reference frame (d-q reference frame), and therefore, run the permanent magnet synchronous motor (PMSM) correctly.


COMPONENT: mcb
EXAMPLENAME: PositionControlPMSMQepExample
EXAMPLETITLE: Position Control of PMSM Using Quadrature Encoder
DESCRIPTION:
Implements the field-oriented control (FOC) technique to control the position of a three-phase permanent magnet synchronous motor (PMSM). The FOC algorithm requires rotor position feedback, which it obtains from a quadrature encoder sensor.


COMPONENT: mcb
EXAMPLENAME: TunePIControllersInFWCModeUsingFOCAutotunerBlockExample
EXAMPLETITLE: Tune PI Controllers (in Field-Weakening Control Mode) Using FOC Autotuner Block
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Simulink Control Design;Embedded Coder;C2000 Microcontroller Blockset;Stateflow

DESCRIPTION:
Uses the Field Oriented Control Autotuner block to compute the gain values of the PI controllers available in the speed, current, and flux control loops of a field-weakening control algorithm. For details about this block, see Field Oriented Control Autotuner.


COMPONENT: mcb
EXAMPLENAME: FWCWithMTPAOfNonlinearSynRMUsingLUTExample
EXAMPLETITLE: Field-Weakening Control (with MTPA) of Nonlinear Synchronous Reluctance Motors Using Lookup Table
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Simscape Electrical
DESCRIPTION:
Uses a lookup table (LUT) for a nonlinear synchronous reluctance motors and controller to run the motor using field-weakening control (with maximum torque per ampere (MTPA)). Use this example to replicate and run a finite element analysis (FEA) based nonlinear, high-fidelity synchronous reluctance motor in simulation. This example helps motor design engineers to simulate high-performance motors in real-world motor control applications. In addition, control system engineers can use this example to design control algorithms for a given set of motor parameter data to achieve high levels of accuracy in tracking and controlling speed and torque as well as to meet efficiency requirements, especially for high-performance motors.


COMPONENT: mcb
EXAMPLENAME: SimulateIpeFwciPMSMPhfoSensorlessEemfExample
PRODUCT: MATLAB;Motor Control Blockset;Simulink
EXAMPLETITLE:
Simulate Initial Position Estimation and Field-Weakening Control of IPMSM Using Pulsating High-Frequency Injection and Extended EMF Observer

DESCRIPTION:
Uses sensorless techniques such as pulsating high-frequency injection and extended EMF observer to estimate and track motor position to simulate interior permanent magnet synchronous motor (IPMSM) operation using field-weakening control (FWC).


COMPONENT: mcb
EXAMPLENAME: DirectTorqueControlOfPMSMQuadratureEncoderFluxObserverExample
EXAMPLETITLE: Direct Torque Control of PMSM Using Quadrature Encoder or Sensorless Flux Observer
DESCRIPTION:
Implements direct torque control (DTC) technique to control the speed of a three-phase permanent magnet synchronous motor (PMSM). Direct Torque Control (DTC) is a vector motor control technique that implements motor speed control by directly controlling the flux and torque of the motor. The example algorithm needs motor currents and position feedback from PMSM. It uses space vector pulse-width modulation (DTC-SVPWM) variant of DTC, which uses space vector modulation (SVM) to produce the pulse-width modulation (PWM) duty cycles that are used by the inverter. For more details about the DTC-SVPWM algorithm used in this example, see Direct Torque Control (DTC).


COMPONENT: mcb
EXAMPLENAME: HallSequenceCalibrationBldcExample
EXAMPLETITLE: Hall Sensor Sequence Calibration of BLDC Motor
DESCRIPTION:
Calculates the Hall sensor sequence with respect to position zero of the rotor in open-loop control. This workflow helps you to spin the motor using six-step commutation without the need to label the hall sensors or derive the switching sequence. Run this example and obtain the hall sequence, and use this hall sequence with the Six Step Commutation block to run the motor in closed loop as explained in Six-Step Commutation of BLDC Motor Using Sensor Feedback example.


COMPONENT: mcb
EXAMPLENAME: HallOffsetExample
EXAMPLETITLE: Hall Offset Calibration for PMSM
DESCRIPTION:
Calculates the offset between the rotor direct axis ( d -axis) and position detected by the Hall sensor. The field-oriented control (FOC) algorithm needs this position offset to run the permanent magnet synchronous motor (PMSM) correctly. To compute the offset, the target model runs the motor in the open-loop condition. The model uses a constant (voltage along the stator's d -axis) and a zero (voltage along the stator's q -axis) to run the motor (at a low constant speed) by using a position or ramp generator. When the position or ramp value reaches zero, the corresponding rotor position is the offset value for the Hall sensors.


COMPONENT: mcb
EXAMPLENAME: IPMSMInitPosEstExample
EXAMPLETITLE: Estimate Initial Rotor Position Using Pulsating High-Frequency and Dual-Pulse Methods
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Embedded Coder;C2000 Microcontroller Blockset;Simscape Electrical

DESCRIPTION:
Estimates the initial position (in electrical radians) of a stationary interior PMSM by using pulsating high-frequency (PHF) injection and dual pulse (DP) techniques.


COMPONENT: mcb
EXAMPLENAME: PMSMSpeedUsingADRCExample
EXAMPLETITLE: Implement PMSM Speed Control Using Active Disturbance Rejection Control
PRODUCT:
MATLAB;Motor Control Blockset;Simulink;Control System Toolbox;Simulink Control Design;Embedded Coder;C2000 Microcontroller Blockset

DESCRIPTION:
Implement active disturbance rejection control (ADRC) of the speed of a permanent magnet synchronous motor (PMSM) modelled in Simulink® using the Active Disturbance Rejection Control (Simulink Control Design) block. You can use the example to implement field-oriented control (FOC) using either a proportional integral (PI) or ADRC-based controller to run the motor in the speed control mode. Therefore, you can compare the performance of the PI and ADRC controllers.


COMPONENT: microbit
EXAMPLENAME: TiltControlBBCMicrobitTargetLEDExample
EXAMPLETITLE: Use Tilt Control on BBC micro:bit to Reach to a Target LED
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Use a Simulink® model to build a simple game that uses tilt control on BBC micro:bit to reach to a target LED on the LED matrix, and see a happy face LED image upon success.


COMPONENT: microbit
EXAMPLENAME: BBCTuneMonitorModelRunningHardwareExample
EXAMPLETITLE: Tune and Monitor Model Running on Hardware
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Use the External mode (Monitor and Tune) to tune parameters and monitor a Simulink® model running on your target hardware.


COMPONENT: microbit
EXAMPLENAME: DiceSimulationLEDMatrixExample
EXAMPLETITLE: Dice Simulation on LED Matrix
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
Develop a Simulink® model to implement a Dice Simulation on BBC micro:bit board using the on board Accelerometer sensor and 5x5 LED Matrix.


COMPONENT: mpc
EXAMPLENAME: VehicleSteeringControlExample
EXAMPLETITLE: Lane Keeping Assist System Using Model Predictive Control
PRODUCT: Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Design an MPC controller that keeps an ego vehicle traveling along the center of a straight or curved road by adjusting the front steering angle.


COMPONENT: mpc
EXAMPLENAME: mpccustomestimation
EXAMPLETITLE: Custom State Estimation
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
You can override the default MPC controller state estimation method by changing the default Kalman gains or by supplying your own controller state estimates.


COMPONENT: mpc
EXAMPLENAME: mpcsubsystemdemo
EXAMPLETITLE: Using MPC Controller Block Inside Function-Call and Triggered Subsystems
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
To ensure that an MPC controller works properly inside a Function-Call or triggered subsystem, configure the MPC Controller block to use inherited sample time and invoke the subsystem periodically with the same sample time defined in the MPC controller object.


COMPONENT: mpc
EXAMPLENAME: ampccstr_linearization
EXAMPLETITLE: Adaptive MPC Control of Nonlinear Chemical Reactor Using Successive Linearization
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Update the internal model of an adaptive MPC controller by linearizing the nonlinear plant at each control interval.


COMPONENT: mpc
EXAMPLENAME: mpcweightsdemo
EXAMPLETITLE: Specifying Alternative Cost Function with Off-Diagonal Weight Matrices
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
You can specify an alternative cost function for your model predictive controller to minimize during optimization.


COMPONENT: mpc
EXAMPLENAME: RunTimeHorizonAdjustmentExample
EXAMPLETITLE: Evaluate Control Performance Using Run-Time Horizon Adjustment
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
You can efficiently evaluate the performance of your MPC controller for various horizon configurations.


COMPONENT: mpc
EXAMPLENAME: ParallelParkingUsingRRTPlannerAndMPCTrackingControllerExample
EXAMPLETITLE: Parallel Parking Using RRT Planner and MPC Tracking Controller
PRODUCT:
MATLAB;Model Predictive Control Toolbox;Optimization Toolbox;Automated Driving Toolbox;Navigation Toolbox;Simulink

DESCRIPTION:
Automatically parallel park a vehicle by generating a path using the RRT star planner and tracking the trajectory using nonlinear model predictive control.


COMPONENT: mpc
EXAMPLENAME: mpccstr
EXAMPLETITLE: Gain-Scheduled MPC Control of Nonlinear Chemical Reactor
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Control a nonlinear chemical reactor using a gain-scheduled model predictive controller as the reactor transitions from one operating condition to another.


COMPONENT: mpc
EXAMPLENAME: NonlinearAndGSMPCControlOfAnEthyleneOxidationPlantExample
EXAMPLETITLE: Nonlinear and Gain-Scheduled MPC Control of an Ethylene Oxidation Plant
PRODUCT: MATLAB;Model Predictive Control Toolbox;Optimization Toolbox;Simulink
DESCRIPTION:
You can generate one or more linear MPC controllers from a nonlinear MPC controller and use these controllers for gain-scheduled control applications.


COMPONENT: mpc
EXAMPLENAME: EconomicMPCControlOfEOExample
EXAMPLETITLE: Economic MPC Control of Ethylene Oxide Production
PRODUCT: Model Predictive Control Toolbox;Optimization Toolbox;Simulink
DESCRIPTION:
Maximize production of an ethylene oxide plant for profit using a nonlinear cost function and nonlinear constraints.


COMPONENT: mpc
EXAMPLENAME: ampccstr_estimation
EXAMPLETITLE: Adaptive MPC Control of Nonlinear Chemical Reactor Using Online Model Estimation
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Update the internal model of an adaptive MPC controller by estimating a plant model at each control interval.


COMPONENT: mpc
EXAMPLENAME: ParkingValetUsingNonlinearModelPredictiveControlExample
EXAMPLETITLE: Parking Valet Using Multistage Nonlinear Model Predictive Control
DESCRIPTION: Design controller for parking garage valet using nonlinear model predictive control.
PRODUCT:
MATLAB;Model Predictive Control Toolbox;Automated Driving Toolbox;Optimization Toolbox;Navigation Toolbox;Simulink


COMPONENT: mpc
EXAMPLENAME: TimeVaryingMPCControlOfATimeVaryingLinearSystemExample
EXAMPLETITLE: Time-Varying MPC Control of a Time-Varying Plant
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Achieve better performance when controlling a time-varying plant by using a prediction model and nominal conditions that vary over the prediction horizon.


COMPONENT: mpc
EXAMPLENAME: empcmotor
EXAMPLETITLE: Explicit MPC Control of DC Servomotor with Constraint on Unmeasured Output
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Design an explicit model predictive controller for a DC servomotor with constraints on the manipulated variable and unmeasured output.


COMPONENT: mpc
EXAMPLENAME: mpcoffsets
EXAMPLETITLE: Design Model Predictive Controller at Equilibrium Operating Point
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
To design an MPC controller at an equilibrium point with nonzero operating conditions, you can specify the corresponding nominal conditions in the controller object.


COMPONENT: mpc
EXAMPLENAME: AdaptiveCruiseControlExample
EXAMPLETITLE: Adaptive Cruise Control System Using Model Predictive Control
PRODUCT: Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Design an MPC controller that tracks a set velocity and maintains a safe distance from a lead vehicle by adjusting the longitudinal acceleration of an ego vehicle.


COMPONENT: mpc
EXAMPLENAME: ScheduleControllersAtMultipleOperatingPointsExample
EXAMPLETITLE: Schedule Controllers at Multiple Operating Points
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Control a nonlinear system by designing multiple MPC controllers for different plant operating conditions.


COMPONENT: mpc
EXAMPLENAME: mpcsequence
EXAMPLETITLE: Understanding Control Behavior by Examining Optimal Control Sequence
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
You can analyze the optimal control sequence computed by a model predictive controller at each sample time.


COMPONENT: mpc
EXAMPLENAME: mpcrtwdemo
EXAMPLETITLE: Simulation and Code Generation Using Simulink Coder
PRODUCT: Model Predictive Control Toolbox;Simulink;Simulink Coder
DESCRIPTION:
Simulate your MPC controller in Simulink and generate real-time code that uses either double-precision or single-precision signals.


COMPONENT: mpc
EXAMPLENAME: SimulateMPCControllerWithACustomQPSolverExample
EXAMPLETITLE: Simulate MPC Controller with a Custom QP Solver
PRODUCT: Model Predictive Control Toolbox;Optimization Toolbox;Simulink
DESCRIPTION:
Simulate the closed-loop response of a model predictive controller with a custom quadratic programming solver.


COMPONENT: mpc
EXAMPLENAME: empcaircraft
EXAMPLETITLE: Explicit MPC Control of an Aircraft with Unstable Poles
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Control an unstable aircraft with saturating actuators using an explicit model predictive controller.


COMPONENT: mpc
EXAMPLENAME: mpcplcdemo
EXAMPLETITLE: Simulation and Structured Text Generation Using Simulink PLC Coder
PRODUCT: Model Predictive Control Toolbox;Simulink PLC Coder;Simulink
DESCRIPTION:
Simulate your MPC controller in Simulink and generate structured text for programmable logic controllers.


COMPONENT: mpc
EXAMPLENAME: mpcoptimalcost
EXAMPLETITLE: Switching Controllers Based on Optimal Costs
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
You can switch between multiple MPC controllers based on their optimal objective function cost values.


COMPONENT: mpc
EXAMPLENAME: ExplicitMPCControlOfAnInvertedPendulumOnACartExample
EXAMPLETITLE: Explicit MPC Control of an Inverted Pendulum on a Cart
PRODUCT: Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Control an inverted pendulum in an unstable equilibrium position using an explicit model predictive controller.


COMPONENT: mpc
EXAMPLENAME: ControlOfRobotManipulatorUsingPassivityBasedNonlinearMPCExample
EXAMPLETITLE: Control Robot Manipulator Using Passivity-Based Nonlinear MPC
PRODUCT: MATLAB;Model Predictive Control Toolbox;Optimization Toolbox
DESCRIPTION:
Enforce stability of a robotic manipulator by implementing passivity-based constraints in a nonlinear MPC controller.


COMPONENT: mpc
EXAMPLENAME: UseSuboptimalSolutionInFastMPCExample
EXAMPLETITLE: Use Suboptimal Solution in Fast MPC Applications
PRODUCT: Model Predictive Control Toolbox;Simulink
DESCRIPTION:
You can guarantee the worst-case execution time for your MPC controller by applying a suboptimal solution after the number of optimization iterations exceeds a specified maximum value.


COMPONENT: mpc
EXAMPLENAME: mpcswitching
EXAMPLETITLE: Gain-Scheduled Implicit and Explicit MPC Control of Mass-Spring System
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Implement gain-scheduled MPC control of a nonlinear plant using the Multiple MPC Controllers block and Multiple Explicit MPC Controllers block.


COMPONENT: mpc
EXAMPLENAME: mpccustomqp
EXAMPLETITLE: Solve Custom MPC Quadratic Programming Problem and Generate Code
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
You can implement a custom MPC control algorithm that supports C code generation in MATLAB using the built-in QP solver, mpcqpsolver .


COMPONENT: mpc
EXAMPLENAME: ControlOfAnInvertedPendulumOnACartExample
EXAMPLETITLE: MPC Control of an Inverted Pendulum on a Cart
PRODUCT: Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Control an inverted pendulum in an unstable equilibrium position using a model predictive controller.


COMPONENT: mpc
EXAMPLENAME: ParallelParkingUsingNonlinearModelPredictiveControlExample
EXAMPLETITLE: Parallel Parking Using Nonlinear Model Predictive Control
DESCRIPTION: Design a parallel parking controller using nonlinear model predictive control.
PRODUCT:
MATLAB;Model Predictive Control Toolbox;Navigation Toolbox;Optimization Toolbox;Automated Driving Toolbox;Simulink


COMPONENT: mpc
EXAMPLENAME: GainScheduledMPCControlOfAnInvertedPendulumOnACartExample
EXAMPLETITLE: Gain-Scheduled MPC Control of an Inverted Pendulum on a Cart
PRODUCT: Model Predictive Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Control an inverted pendulum in an unstable equilibrium position using a gain-scheduled model predictive controller.


COMPONENT: mpc
EXAMPLENAME: LandingRocketWithMPCExample
EXAMPLETITLE: Landing a Vehicle Using Multistage Nonlinear MPC
PRODUCT: MATLAB;Model Predictive Control Toolbox;Optimization Toolbox;Simulink
DESCRIPTION:
Plan an optimal rocket lander trajectory and perform closed-loop control of landing process using multistage nonlinear MPC.


COMPONENT: mpc
EXAMPLENAME: ParallelParkingOfTruckTrailerUsingMultistageNonlinearMPCExample
EXAMPLETITLE: Parallel Parking of Truck-Trailer Using Multistage Nonlinear MPC
PRODUCT: MATLAB;Model Predictive Control Toolbox;Optimization Toolbox
DESCRIPTION:
Parallel park a truck-trailer system using multistage nonlinear MPC controllers for path planning and trajectory tracking.


COMPONENT: mpc
EXAMPLENAME: mpcmiso
EXAMPLETITLE: Model Predictive Control of Multi-Input Single-Output Plant
PRODUCT: Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Create and simulate a model predictive controller for a plant with multiple inputs and a single output.


COMPONENT: mpc
EXAMPLENAME: TimeVaryingMPCControlOfPendulumExample
EXAMPLETITLE: Time-Varying MPC Control of an Inverted Pendulum on a Cart
PRODUCT: Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Control an inverted pendulum in an unstable equilibrium position using a linear time-varying model predictive controller.


COMPONENT: mpc
EXAMPLENAME: SwingupControlOfPendulumUsingNMPCExample
EXAMPLETITLE: Swing-Up Control of a Pendulum Using Nonlinear Model Predictive Control
PRODUCT: Model Predictive Control Toolbox;Optimization Toolbox;Simulink
DESCRIPTION:
Achieve swing-up and balancing control of an inverted pendulum on a cart using a nonlinear model predictive controller.


COMPONENT: mpc
EXAMPLENAME: mpcutarget
EXAMPLETITLE: Setting Targets for Manipulated Variables
PRODUCT: MATLAB;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
If your plant has more manipulated variables than outputs, you can hold the excess manipulated variables at target values for economical or operational reasons.


COMPONENT: mpc
EXAMPLENAME: ObstacleAvoidingUsingAdaptiveMPCExample
EXAMPLETITLE: Obstacle Avoidance Using Adaptive Model Predictive Control
PRODUCT: Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Use adaptive MPC to make a vehicle follow a reference velocity and avoid obstacles by updating the plant model and linear mixed input/output constraints at run time.


COMPONENT: mpc
EXAMPLENAME: ControlHouseHeatingSystemUsingMPCExample
DESCRIPTION: Design a Multistage MPC controller using a neural state space prediction model.
EXAMPLETITLE:
Control House Heating System Using Nonlinear Model Predictive Control With Neural State-Space Prediction Model

PRODUCT:
MATLAB;Model Predictive Control Toolbox;System Identification Toolbox;Deep Learning Toolbox;Simscape


COMPONENT: msblks
EXAMPLENAME: DesignAndEvaluateBinaryWeightedDACExample
EXAMPLETITLE: Design and Evaluate Binary Weighted DAC
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Design and evaluate a binary weighted DAC using reference architecture and validate the DAC using the DAC Testbench. For this example, use the datasheet of TLC5615. This is a commercial, off-the-shelf 10-bit DAC from Texas Instrument with an update rate of 1.21 MHz.


COMPONENT: msblks
EXAMPLENAME: EffectOfMetastabilityImpairmentInFlashADCExample
EXAMPLETITLE: Effect of Metastability Impairment in Flash ADC
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Customize a flash Analog to Digital Converter (ADC) by adding the metastability probability as an impairment. You can measure the metastability probability impairment to validate your implementation. The example also shows the effect of metastability on the dynamic performance of the flash ADC. When the digital output from a comparator is ambiguous (neither zero nor one), the output is defined as metastable. The ambiguous output is expressed as NaN . This example model uses a MATLAB function block to add the metastability impairment to a flash ADC architecture. Another subsystem reports the metastability probability on the fly.


COMPONENT: msblks
EXAMPLENAME: FindingVoltageSensitivityAndQuiescentFrequencyOfVCOExample
EXAMPLETITLE: Finding Voltage Sensitivity and Quiescent Frequency of VCO
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Find VCO metrics such as voltage sensitivity (Kvco) and quiescent frequency or free running frequency (Fo).


COMPONENT: msblks
EXAMPLENAME: FractionalClockDividerWithAccumulatorExample
EXAMPLETITLE: Frequency Division Using Fractional Clock Divider with Accumulator
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Open the model fractionalClockDivider_w_Accumulator . The model consists of a Pulse Generator and a Fractional Clock Divider with Accumulator block.


COMPONENT: msblks
EXAMPLENAME: HistogramADCLinearityExample
EXAMPLETITLE: ADC Linearity Measurement Using Histogram
PRODUCT: MATLAB;Mixed-Signal Blockset;DSP System Toolbox;Simulink
DESCRIPTION:
Statistical measurement of ADC Linearity is popular in physical systems due to its noise tolerance and relative simplicity of implementation in a physical environment. This example covers problems inherent to statistical linearity measurements and some possible solutions for implementing these measurements in Simulink®.


COMPONENT: msblks
EXAMPLENAME: SARIdealCompareExample
EXAMPLETITLE: Compare SAR ADC to Ideal ADC
PRODUCT: MATLAB;Mixed-Signal Blockset;DSP System Toolbox;Simulink
DESCRIPTION:
A comparison of the SAR ADC from the Mixed-Signal Blockset™ to the ideal ADC model with impairments presented in Analyzing Simple ADC with Impairments.


COMPONENT: msblks
EXAMPLENAME: FractionalClockDividerWithDSMExample
EXAMPLETITLE: Frequency Division Using Fractional Clock Divider with DSM
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Open the model fractionalClockDivider_w_DSM . The model consists of a Pulse Generator and a Fractional Clock Divider with Accumulator block.


COMPONENT: msblks
EXAMPLENAME: DefineOutputSamplesInLowpassResamplerExample
EXAMPLETITLE: Define Output Samples in Lowpass Resampler
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
To demonstrate the variable step discrete behavior of the Lowpass Resampler block, open the model LowpassResamplerOutputSampling .


COMPONENT: msblks
EXAMPLENAME: TunePhaseLockedLoopUsingLoopShapingDesignExample
EXAMPLETITLE: Tune Phase-Locked Loop Using Loop-Shaping Design
PRODUCT: MATLAB;Mixed-Signal Blockset;Control System Toolbox;Simulink
DESCRIPTION:
Tune the components of a passive loop filter to improve the loop bandwidth of a phase-locked loop system.


COMPONENT: msblks
EXAMPLENAME: ModelMASHAndSMASHDeltaSigmaModulatorsExample
EXAMPLETITLE: Model MASH and SMASH Delta Sigma Modulators
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Model multi-stage noise-shaping (MASH) or cascade Delta Sigma Modulators (DSM) using the Delta-Sigma Modulator block. MASH structures work by feeding the quantization error from the present stage to the next stage and combining the outputs from multiple stages in a digital cancellation logic. The advantage of cascade DSMs is that you can get the performance of higher order DSM without their stability issues.


COMPONENT: msblks
EXAMPLENAME: PLLDesignAndVerificationUsingDataSheetSpecificationsExample
EXAMPLETITLE: PLL Design and Verification Using Data Sheet Specifications
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Use Mixed-Signal Blockset™ to model a commercial off-the-shelf integer-N phase-locked loop (PLL) with dual modulus prescaler operating around 4 GHz. You can verify the PLL performance, including phase noise.


COMPONENT: msblks
EXAMPLENAME: SimpleADCImpairmentsExample
EXAMPLETITLE: Analyzing Simple ADC with Impairments
PRODUCT: MATLAB;Mixed-Signal Blockset;DSP System Toolbox;Simulink
DESCRIPTION:
Implement a basic ADC using a Zero-Order Hold block as a sampler. This simple ADC highlights some of the typical impairments introduced in an analog-to-digital converters such as aperture jitter, nonlinearity, quantization, and saturation. This example shows how to measure the effects of such impairments using a Spectrum Analyzer block and the ADC AC Measurement block from the Mixed-Signal Blockset™. To better approximate real-world performance, you can individually enable the impairments in the model.


COMPONENT: msblks
EXAMPLENAME: ModelPLLsInThePhaseDomainExample
EXAMPLETITLE: Model PLLs in the Phase Domain
PRODUCT: MATLAB;Mixed-Signal Blockset;Control System Toolbox
DESCRIPTION:
Model a phase-locked loop (PLL) in the phase domain, compare the analytic results to simulation results in the time domain, and identify the advantages and disadvantages of each approach. Most PLL analysis is performed in the phase domain, and this example shows you how to produce a complete analysis using a minimum of time and effort.


COMPONENT: msblks
EXAMPLENAME: BoostPowerTrainDesignWorkflowExample
EXAMPLETITLE: Boost Power Train Design Workflow
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Design a power supply with a boost power train for a specific operating point, control the output voltage, and perform time-domain simulations.


COMPONENT: msblks
EXAMPLENAME: InvertingAmplifierExample
EXAMPLETITLE: Design Inverting Amplifier
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Model an inverting amplifier circuit using the Operational Amplifier block and the Linear Circuit wizard block.


COMPONENT: msblks
EXAMPLENAME: MeasureTimingMetricsOfPeriodicSignalExample
EXAMPLETITLE: Measure Timing Metrics of Periodic Signal
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Measure the period, frequency, rise time, fall time, and duty cycle of a periodic signal. Also measure the delay of the input signal with respect to a reference signal


COMPONENT: msblks
EXAMPLENAME: CircuitDesignAffectsPLLPerformanceExample
EXAMPLETITLE: Circuit Design Details Affect PLL Performance
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Use the Linear Circuit Wizard block to evaluate the effect of loop filter circuit design details on the performance of a phase-locked loop.


COMPONENT: msblks
EXAMPLENAME: DesignAndEvaluateSimplePLLModelExample
EXAMPLETITLE: Design and Evaluate Simple PLL Model
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Design a simple phase-locked loop (PLL) using a reference architecture and validate it using PLL Testbench.


COMPONENT: msblks
EXAMPLENAME: PhaseNoiseAtPLLOutputExample
EXAMPLETITLE: Phase Noise at PLL Output
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Predict the phase noise at the output of a phase-locked loop (PLL), simulate the PLL using the PLL Testbench, and compare the simulation results to theoretical predictions.


COMPONENT: msblks
EXAMPLENAME: BuckPowerTrainDesignWorkflowExample
EXAMPLETITLE: Buck Power Train Design Workflow
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Use the MathWorks® switched mode power supply (SMPS) workflow to design a power supply with a buck power train.


COMPONENT: msblks
EXAMPLENAME: BoostPowerTrainOperatingPointAnalysisExample
EXAMPLETITLE: Boost Power Train Operating Point Analysis
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Analyze the operating point of a power train for a boost switched-mode power supply (SMPS) using the Linear Circuit Wizard block from the Mixed-Signal Blockset™.


COMPONENT: msblks
EXAMPLENAME: DigitalPhaseLockedLoopExample
EXAMPLETITLE: Digital Phase Locked Loop
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Model a digital phase locked loop using the Mixed-Signal Blockset™. In a digital phase locked loop, phase detection is performed by a time to digital converter (TDC), loop filtering is performed by a digital filter, and the oscillator is a digitally controlled oscillator (DCO). This example demonstrates a behavioral model of a TDC, using the BiquadFilter from the DSP System Toolbox™ as the digital loop filter, and using VCOs and DACs from the Mixed-Signal Blockset to model the DCO.


COMPONENT: msblks
EXAMPLENAME: SingleModulusPrescalerExample
EXAMPLETITLE: Frequency Division Using Single Modulus Prescaler
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Open the model singleModulusPrescaler . The model consists of a Pulse Generator and a Single Modulus Prescaler block.


COMPONENT: msblks
EXAMPLENAME: MeasureACPerformanceMetricsOfBinaryWeightedDACExample
EXAMPLETITLE: Measure AC Performance Metrics of Binary Weighted DAC
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Find the AC performance metrics such as SNR, SINAD, SFDR, ENOB, noise floor and settling time of a binary weighted DAC block.


COMPONENT: msblks
EXAMPLENAME: MixedSignalBlocksetInterleavedADCExample
EXAMPLETITLE: Design and Evaluate Interleaved ADC
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink;DSP System Toolbox
DESCRIPTION:
This interleaved ADC model highlights some of the typical impairments introduced by data converters and their effects on a larger system.


COMPONENT: msblks
EXAMPLENAME: MeasureACPerformanceMetricsOfDACUsingDACACMeasurementExample
EXAMPLETITLE: Measure AC Performance Metrics of DAC Using DAC AC Measurement
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Find the AC performance metrics such as SNR, SINAD, SFDR, ENOB, and noise floor using a DAC AC Measurement block.


COMPONENT: msblks
EXAMPLENAME: InterleavedADCSystemObjectExample
EXAMPLETITLE: Design and Evaluate Interleaved ADC Using System Object
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Use System objects to model and evaluate the performance of an interleaved ADC. This example is based on the AD9625 from Analog Devices.


COMPONENT: msblks
EXAMPLENAME: OffsetErrorAndGainErrorExample
EXAMPLETITLE: Measuring Offset and Gain Errors in ADC
PRODUCT: MATLAB;Mixed-Signal Blockset;DSP System Toolbox;Simulink
DESCRIPTION:
How offset error and gain error are calculated and how each affects the transfer curve of an ADC. Offset error and gain error characterize part of the linearity error in an ADC.


COMPONENT: msblks
EXAMPLENAME: DigitalTimingUsingFixedStepSamplingExample
EXAMPLETITLE: Digital Timing Using Fixed Step Sampling
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Model a three-stage ring oscillator using a combination of fixed-step and variable-step discrete sample times.


COMPONENT: msblks
EXAMPLENAME: ModelAContinuoustimeDSMExample
EXAMPLETITLE: Model a Continuous-Time Delta Sigma Modulator With Inherent Anti-Aliasing Property
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Design a Continuous-time Delta Sigma Modulator (CT DSM) using the DT-CT Translation method explained in [1]. CT DSMs can also be designed using Direct Synthesis of CT DSMs [2].


COMPONENT: msblks
EXAMPLENAME: PhaseNoiseAnalysisInVCOExample
EXAMPLETITLE: Phase Noise Analysis in VCO
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Measure and analyze the effect of phase noise in a voltage controlled oscillator (VCO). Using a VCO block and VCO testbench, this example defines the typical phase noise levels from datasheet specifications and validates the VCO.


COMPONENT: msblks
EXAMPLENAME: AnalyzeTCoilCircuitExample
EXAMPLETITLE: Analyze T-Coil Circuit
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Use the Linear Circuit Wizard block to analyze a T-coil impedance matching circuit and generate S-parameter data from the result.


COMPONENT: msblks
EXAMPLENAME: DualModulusPrescalerExample
EXAMPLETITLE: Frequency Division Using Dual Modulus Prescaler
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Open the model Dual_Modulus_Prescaler_Ex . The model consists of a Pulse Generator and a Dual Modulus Prescaler block.


COMPONENT: msblks
EXAMPLENAME: ThirdOrderDeltaSigmaAdcExample
EXAMPLETITLE: Third Order Delta Sigma ADC
PRODUCT: MATLAB;Mixed-Signal Blockset;DSP System Toolbox;Simscape;Simulink
DESCRIPTION:
Model a 3rd order Delta Sigma ADC and measure its performance using the ADC AC Measurement block. This ADC model consists of a behavioral model of a delta sigma ADC that uses a 3rd order feedforward modulator. The ADC input sample rate is 64 MHz and after decimating filters, the output sample rate is 1 MHz.


COMPONENT: msblks
EXAMPLENAME: ModelComparatorWithHysteresisUsingOperationalAmplifierExample
EXAMPLETITLE: Model Comparator with Hysteresis Using Operational Amplifier
PRODUCT: MATLAB;Mixed-Signal Blockset
DESCRIPTION:
Model an analog comparator with hysteresis using the Operational Amplifier block from Mixed-Signal Blockset™.


COMPONENT: msblks
EXAMPLENAME: DesignAndEvaluateSegmentedDACExample
EXAMPLETITLE: Design and Evaluate Segmented DAC
PRODUCT: MATLAB;Mixed-Signal Blockset;Simulink
DESCRIPTION:
Design and evaluate a segmented DAC using reference architecture and validate the DAC using the DAC Testbench. For this example, use the datasheet of AD9775. This is a commercial, off-the-shelf 14-bit DAC from Analog Devices.


COMPONENT: msblks
EXAMPLENAME: MeasuringACMetricsOfAFourthOrderDeltaSigmaADCExample
EXAMPLETITLE: AC Metrics of Fourth Order Delta Sigma ADC
PRODUCT: MATLAB;Mixed-Signal Blockset;DSP System Toolbox;Simulink
DESCRIPTION:
Model a fourth order delta sigma ADC and measure its AC metrics. The ADC AC Measurement block from the Mixed-Signal Blockset™ is used to measure the AC performance of the ADC. AC measurements are essential to measure the metrics like SNR and ENOB inform the designer whether optimal performance is being achieved by the design. If not, the designer can tweak the design parameters to make the better.


COMPONENT: multibody_deeplearning
EXAMPLENAME: TrainHumanoidWalkerExample
EXAMPLETITLE: Train Humanoid Walker
DESCRIPTION: Train a humanoid robot to walk using either a genetic algorithm or reinforcement learning.
PRODUCT:
MATLAB;Simscape Multibody;Reinforcement Learning Toolbox;Global Optimization Toolbox;Deep Learning Toolbox;Simulink


COMPONENT: nav
EXAMPLENAME: PathFollowingWithObstacleAvoidanceInSimulinkExample
EXAMPLETITLE: Path Following with Obstacle Avoidance in Simulink®
PRODUCT: Navigation Toolbox;ROS Toolbox;Robotics System Toolbox;Simulink
DESCRIPTION:
Use Simulink to avoid obstacles while following a path for a differential drive robot. This example uses ROS to send and receive information from a MATLAB®-based simulator. You can replace the simulator with other ROS-based simulators such as Gazebo®.


COMPONENT: nav
EXAMPLENAME: ModelAndControlAutonomousVehicleInOffroadScenarioExample
EXAMPLETITLE: Model and Control Autonomous Vehicle in Offroad Scenario
PRODUCT:
MATLAB;Navigation Toolbox;Simulink;Automated Driving Toolbox;Image Processing Toolbox;Computer Vision Toolbox;Stateflow

DESCRIPTION:
Integrate route, terrain-aware, and local planners into a model and simulate the haul truck in a simulated offroad scenario.


COMPONENT: nav
EXAMPLENAME: ComputeOrientationFromRecordedIMUDataBlockExample
EXAMPLETITLE: Compute Orientation from Recorded IMU Data
PRODUCT: MATLAB;Navigation Toolbox;Simulink
DESCRIPTION:
Load the rpy_9axis file into the workspace. The file contains recorded accelerometer, gyroscope, and magnetometer sensor data from a device oscillating in pitch (around the y -axis), then yaw (around the z -axis), and then roll (around the x -axis). The file also contains the sample rate of the recording.


COMPONENT: nav_robotics
EXAMPLENAME: ConvertCoordinateSystemTransformationsExample
EXAMPLETITLE: Convert Coordinate System Transformations
PRODUCT: MATLAB;Simulink;Navigation Toolbox;Robotics System Toolbox
DESCRIPTION:
How to convert some basic coordinate system transformations into other coordinate systems using Coordinate Transformation Conversion block. Input vectors are expected to be vertical vectors.


COMPONENT: nucleo
EXAMPLENAME: GettingStartedSimulinkCoderSpkgSTMsNucleoBoardsExample
EXAMPLETITLE: Getting Started with Simulink Coder Support Package Using STMicroelectronics Nucleo Boards
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Demonstrates how to use the Simulink® Coder™ Support Package for STMicroelectronics® Nucleo Boards to run a Simulink® model on an STMicroelectronics Nucleo board.


COMPONENT: nucleo
EXAMPLENAME: ChangeLEDGlowIntensitySTMNucleoBoardsExample
EXAMPLETITLE: Change the LED Glow Intensity on STMicroelectronics Nucleo Boards
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Demonstrates how to use the Simulink® Coder™ Support Package to run a Simulink model on an STMicroelectronics® Nucleo board to brighten and dim an LED.


COMPONENT: nucleo
EXAMPLENAME: ReadAccelerometerGyrometerDataSTMNucleoUsingSCIExample
EXAMPLETITLE: Read Accelerometer and Gyrometer Data from an STMicroelectronics Nucleo Board Using SCI Blocks
PRODUCT: MATLAB;Simulink Coder;Simulink
DESCRIPTION:
Use Simulink® Coder™ Support Package to send data to your computer from a STMicroelectronics® Nucleo board and read it using serial (SCI) blocks.


COMPONENT: nucleo
EXAMPLENAME: ParamTuningSignalLogSerialExtSTMNucleoBoardExample
PRODUCT: MATLAB
EXAMPLETITLE:
Parameter Tuning and Signal Logging with Universal Measurement and Calibration Protocol Using STMicroelectronics Nucleo Boards

DESCRIPTION:
Tune the parameters and monitor the signals of an algorithm running on an STMicroelectronics® Nucleo board.


COMPONENT: nucleo
EXAMPLENAME: ReadDataFromI2CbasedSensorsUsingSTMNucleoBoardExample
EXAMPLETITLE: Read Data from I2C-Based Sensors Using STMicroelectronics Nucleo Boards
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Use the Simulink® Coder™ Support Package for configuring and reading data from an I2C-based sensor using an STMicroelectronics® Nucleo board.


COMPONENT: nucleo
EXAMPLENAME: MODBUSRS485CommunicationNucleoExample
EXAMPLETITLE: MODBUS RS485 Communication Between Client and Server Devices Using STMicroelectronics Nucleo Boards
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Use the Simulink® Coder™ Support Package for STMicroelectronics® Nucleo Boards to implement a MODBUS® RS485 asynchronous, serial communication between MODBUS client and server devices. It also shows the four modes of operation: Client Read, Client Write, Server Read, and Server Write.


COMPONENT: nucleo
EXAMPLENAME: ECGSignalProcessingUsingSTMicroelectronicsNucleoBoardExample
EXAMPLETITLE: ECG Signal Processing using STMicroelectronics Nucleo Board
PRODUCT: MATLAB;Simulink;Simulink Coder;DSP System Toolbox
DESCRIPTION:
Use the STM32 Nucleo F767ZI board to process an ECG signal input from an ECG sensor, extract the heart rate in beats per minutes (bpm), and send the ECG signal and heart rate to the ThingSpeak internet of things (IoT) analytics platform service.


COMPONENT: nucleo
EXAMPLENAME: CommunicatingWithAnSPIBasedEEPROMUsingSTMNucleoBoardExample
EXAMPLETITLE: Communicating with an SPI Based EEPROM Using the STMicroelectronics Nucleo Board
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Use Simulink® Coder™ Support Package for STMicroelectronics® Nucleo Boards to enable and write to/ read from an SPI based EEPROM.


COMPONENT: nucleo
EXAMPLENAME: ImpactDetectionLIS3DHExample
EXAMPLETITLE: Impact Detection Using LIS3DH Inertial Wakeup Interrupt
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Coder™ Support Package for STMicroelectronics® Nucleo Boards to sense the impact of the sensor using the Inertial wake-up interrupt of LIS3DH linear accelerometer connected to a STMicroelectronics Nucleo board.


COMPONENT: nucleo
EXAMPLENAME: ControlRotaryEncoderKnobUsingStmNucleoBoardExample
EXAMPLETITLE: Control Rotary Encoder Knob Using STMicroelectronics Nucleo Board
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Use the Simulink Coder® Support Package for STMicroelectronics STM32 Nucleo board to control a 12-step rotary encoder with a built-in push button.


COMPONENT: nucleo
EXAMPLENAME: CodeVerificationValidationProcessorLoopPILSimulationExample
EXAMPLETITLE: Code Verification and Validation with Processor-in-the-Loop (PIL) Simulation
PRODUCT: MATLAB
DESCRIPTION:
Use Simulink® Coder™ Support Package for code verification and validation with PIL using STMicroelectronics® Nucleo Boards. The PIL feature requires Embedded Coder®.


COMPONENT: nucleo
EXAMPLENAME: TripleAxisTiltLIS3DHFIFOExample
EXAMPLETITLE: Triple-Axis Tilt Calculation Using LIS3DH FIFO Data Ready Interrupt
PRODUCT: MATLAB
DESCRIPTION:
Use the FIFO data ready interrupt of LIS3DH linear accelerometer connected to a STMicroelectronics Nucleo board to sense the tilt of the sensor. This is done using a downstream function-call subsystem that reads acceleration values from FIFO buffer sensor.


COMPONENT: nucleo
EXAMPLENAME: ClickDetectionLIS3DHExample
EXAMPLETITLE: Single Click and Double Click Detection Using LIS3DH Single Click Interrupt
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Use the Simulink® Coder™ Support Package for STMicroelectronics® Nucleo Boards to sense the free-fall of the sensor using the Single Click interrupt of LIS3DH linear accelerometer connected to a STMicroelectronics Nucleo board.


COMPONENT: nucleo
EXAMPLENAME: FreeFallDetectionLIS3DHExample
EXAMPLETITLE: Free-Fall Detection Using LIS3DH Freefall Application Interrupt
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Use the Simulink® Coder™ Support Package for STMicroelectronics® Nucleo Boards to sense the free-fall of the sensor using the Inertial freefall application interrupt of LIS3DH linear accelerometer connected to a STMicroelectronics Nucleo board.


COMPONENT: nucleo
EXAMPLENAME: TriggerFunctionCallNucleoDataReadyBMI160Example
PRODUCT: MATLAB;Simulink;Simulink Coder
EXAMPLETITLE:
Trigger Downstream Function-Call Subsystem Using STMicroelectronics Nucleo External Interrupt Block with Data Ready Event on BMI160 Sensor

DESCRIPTION:
Use the Simulink® Coder™ Support Package for STMicroelectronics® Nucleo Boards to trigger a downstream function-call in Monitor and Tune action when a Data ready event occurs on BMI160 sensor using a ST Nucleo External Interrupt block. This example model for monitor and tune simulation, shows the capabilities of the External Interrupt block during data ready event on BMI160 sensor.


COMPONENT: nucleo
EXAMPLENAME: IdentifyPunchFlexHandGestMachLearnAlgOnStmNucleoBdExample
PRODUCT: MATLAB;Simulink;Simulink Coder;Statistics and Machine Learning Toolbox
EXAMPLETITLE:
Identify Punch and Flex Hand Gestures Using Machine Learning Algorithm on STMicroelectronics Nucleo Boards

DESCRIPTION:
Use the Simulink® Coder Support Package for STMicroelectronics® Nucleo boards to identify punch and flex hand gestures using a machine learning algorithm. The example is deployed on an STM Nucleo board that uses an external sensor (LSM6DSL) available in sensor shield (X-NUCLEO-IKS01A2) to identify the hand gestures. The output from the machine learning algorithm, after identifying whether a hand gesture is a punch or a flex, is transmitted to the serial port where 0 represents a punch and 1 represents a flex.


COMPONENT: nvidia
EXAMPLENAME: SendAndReceiveMAVLinkPacketsExample
EXAMPLETITLE: Send and Receive MAVLink Packets on Jetson Boards
PRODUCT: MATLAB;Simulink Coder;Simulink;MATLAB Coder;UAV Toolbox;Instrument Control Toolbox
DESCRIPTION:
Use MATLAB® Coder™ Support Package for NVIDIA® Jetson® and NVIDIA DRIVE® to send and receive MAVLink packets on a Jetson board via serial from a Pixhawk board.


COMPONENT: nvidia
EXAMPLENAME: TrafficMonitoringApplicationUsingDeeplearningOnJetsonExample
EXAMPLETITLE: Deep Learning Vehicle Detector from IP Camera Stream on Jetson
PRODUCT: MATLAB;GPU Coder;Computer Vision Toolbox;Simulink;Deep Learning Toolbox
DESCRIPTION:
Develop a CUDA® application from a Simulink® model that performs vehicle detection using convolutional neural networks (CNN). This example takes the IP camera stream as an input, and detects vehicles in the frame. This example uses the pretrained vehicle detection network from the Object Detection Using YOLO v2 Deep Learning example of the Computer Vision toolbox™. For more information, see Object Detection Using YOLO v2 Deep Learning (Computer Vision Toolbox).


COMPONENT: nvidia
EXAMPLENAME: CANCommunicationOnNvidiaJetsonExample
EXAMPLETITLE: CAN Bus Communication on NVIDIA Jetson TX2 in Simulink
PRODUCT: MATLAB;MATLAB Coder;GPU Coder;Deep Learning Toolbox;Computer Vision Toolbox
DESCRIPTION:
Deploy a Simulink® model that uses CAN communication for a deep learning application. The Simulink model in this example uses the CAN Transmit and CAN Receive blocks from the MATLAB® Coder™ Support Package for NVIDIA® Jetson® and NVIDIA DRIVE® Platforms to model a CAN bus system on the Jetson TX2 platform. The model uses the CAN bus to transmit the recognized traffic sign objects in a video frame from one CAN node to another CAN node.


COMPONENT: nvidia
EXAMPLENAME: PublishAndSubscribeToMessagesOnThingSpeakUsingMQTTBlocksExample
EXAMPLETITLE: Publish and Subscribe to Messages on ThingSpeak Using MQTT Blocks
PRODUCT: MATLAB;Simulink Coder
DESCRIPTION:
Communicate using the Message Queuing Telemetry Transport (MQTT) on NVIDIA® Jetson® and DRIVE® platforms.


COMPONENT: nvidia
EXAMPLENAME: ClassifyWebcamImagesOnNVIDIAJetsonFromSimulinkExample
EXAMPLETITLE: Deploy and Classify Webcam Images on NVIDIA Jetson Platform from Simulink
PRODUCT: MATLAB;Computer Vision Toolbox;Embedded Coder;GPU Coder;MATLAB Coder;Simulink;Simulink Coder
DESCRIPTION:
Deploy a Simulink® model on the NVIDIA® Jetson™ board for classifying webcam images. This example classifies images from a webcam in real-time by using the pretrained deep convolutional neural network, ResNet-50 . The Simulink model in the example uses the camera and display blocks from the MATLAB® Coder™ Support Package for NVIDIA Jetson and NVIDIA DRIVE™ Platforms to capture the live video stream from a webcam and display the prediction results on a monitor connected to the Jetson platform.


COMPONENT: nvidia
EXAMPLENAME: KeywordSpottingInAudioUsingLSTMNetworksOnNVIDIAJetsonExample
EXAMPLETITLE: Keyword Spotting in Audio Using MFCC and LSTM Networks on NVIDIA Embedded Hardware from Simulink
PRODUCT: MATLAB;Audio Toolbox;Deep Learning Toolbox;Simulink Coder
DESCRIPTION:
Deploy a Simulink® model on the NVIDIA® Jetson™ board for keyword spotting in audio data. This example identifies the keyword( YES ) in the input audio data using Mel Frequency Cepstral Coefficients (MFCC) and a pretrained Bidirectional Long Short-Term Memory (BiLSTM) network.


COMPONENT: nvidia
EXAMPLENAME: SendAndReceiveDataOverUDPExample
EXAMPLETITLE: Send and Receive Data over UDP on NVIDIA Jetson Platforms
PRODUCT: MATLAB;Simulink;Simulink Coder;MATLAB Coder
DESCRIPTION:
Use MATLAB® Coder™ Support Package for NVIDIA® Jetson® and NVIDIA DRIVE® to send and receive UDP data over the network on a Jetson board.


COMPONENT: nvidia
EXAMPLENAME: StreamImagesFromNVIDIAJetsonXavierNXUsingROSExample
EXAMPLETITLE: Stream Images from NVIDIA Jetson Xavier NX using Robot Operating System (ROS)
PRODUCT: MATLAB Coder;ROS Toolbox;Simulink
DESCRIPTION:
Stream images captured from a webcam on NVIDIA® Jetson Xavier NX board to the host computer using ROS communication interface.


COMPONENT: nvidia
EXAMPLENAME: StitchingMultipleCamerasImagesNVIDIAJetsonBoardGPUCoderExample
EXAMPLETITLE: Capturing and Stitching Images from Multiple Cameras on NVIDIA Jetson
PRODUCT: MATLAB;Simulink;Simulink Coder;GPU Coder
DESCRIPTION:
Acquire images from two cameras connected to an NVIDIA® Jetson™ board and stitch them together to generate a composite image.


COMPONENT: nvidia
EXAMPLENAME: ReadAndWriteSerialDataExample
EXAMPLETITLE: Read and Write Data over Serial Port on NVIDIA Jetson Platforms
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Use MATLAB® Coder™ Support Package for NVIDIA® Jetson® and NVIDIA DRIVE® to read and write serial data over the UART port on a Jetson board.


COMPONENT: nvidia
EXAMPLENAME: MODBUSTCPIPCommMasterAndSlaveDevicesUsingNVIDIAJetsonTX2Example
EXAMPLETITLE: MODBUS TCP/IP Communication Between Client and Server Devices Using NVIDIA Jetson TX2 Hardware
PRODUCT: MATLAB
DESCRIPTION:
Use the MATLAB® Coder™ Support Package for NVIDIA® Jetson® and NVIDIA DRIVE® Platforms to implement MODBUS® TCP/IP communication between MODBUS client and server devices. It also shows how to communicate between the two devices in four modes of operation, Client Read, Client Write, Server Read, and Server Write.


COMPONENT: optim
EXAMPLENAME: VectorizedSurrogateOptimizationParallelExample
EXAMPLETITLE: Vectorized Surrogate Optimization for Custom Parallel Simulation
PRODUCT: MATLAB;Optimization Toolbox;Global Optimization Toolbox;Parallel Computing Toolbox;Simulink
DESCRIPTION:
Perform custom parallel optimization using the surrogateopt UseVectorized and BatchUpdateInterval options.


COMPONENT: pde
EXAMPLENAME: ThermalAnalysisOfDiscBrakeExample
EXAMPLETITLE: Thermal Analysis of Disc Brake
PRODUCT: MATLAB;Partial Differential Equation Toolbox;Simulink
DESCRIPTION:
Use Partial Differential Equation Toolbox and Simscape Driveline to simulate a brake pad moving around a disc and analyze temperatures when braking.


COMPONENT: phased
EXAMPLENAME: slexPRFSelectionSEExampleExample
EXAMPLETITLE: Waveform Scheduling Based on Target Detection
PRODUCT: Phased Array System Toolbox;SimEvents;Simulink
DESCRIPTION:
In radar operation, it is often necessary to adjust the operation mode based on the target return. This example shows how to model a radar that changes its pulse repetition frequency (PRF) based on the radar detection.


COMPONENT: phased
EXAMPLENAME: PhaseShiftBeamformingOfPlaneWaveSignalExample
EXAMPLETITLE: Phase-Shift Beamforming of Plane Wave Signal
PRODUCT: DSP System Toolbox;MATLAB;Phased Array System Toolbox;Signal Processing Toolbox;Simulink
DESCRIPTION:
Beamform a plane wave arriving at a 10 element ULA of isotropic antenna elements. All the signals are delayed by 100 samples. The operating frequency of the array is 100 MHz.


COMPONENT: phased
EXAMPLENAME: DataflowMonostaticRadarSystemExample
EXAMPLETITLE: Multicore Simulation of Test Signals for a Radar Receiver
PRODUCT: DSP System Toolbox;MATLAB;Phased Array System Toolbox;Simulink
DESCRIPTION:
Simulates a monostatic radar system. It uses dataflow domain in Simulink® to automatically partition the data-driven portions of the radar system into multiple threads and thereby improving the performance of the simulation by executing it on your desktop's multiple cores.


COMPONENT: phased
EXAMPLENAME: RadarEquationToRFComponentsExample
EXAMPLETITLE: Radar Design from Radar Equation to RF Components
PRODUCT: MATLAB;RF Blockset;Phased Array System Toolbox
DESCRIPTION:
Model radars at increasing levels of fidelity using Radar Designer, radar budget plot, and transmitters and receivers.


COMPONENT: phased
EXAMPLENAME: slexBeamformerExampleExample
EXAMPLETITLE: Conventional and Adaptive Beamformers
PRODUCT: Phased Array System Toolbox;Simulink
DESCRIPTION:
Apply conventional and adaptive beamforming in Simulink® to a narrowband signal received by an antenna array. The signal model includes noise and interference. This example is based on the Conventional and Adaptive Beamformers example.


COMPONENT: phased
EXAMPLENAME: slexMonostaticRadarExampleExample
EXAMPLETITLE: Simulating Test Signals for a Radar Receiver in Simulink
PRODUCT: Phased Array System Toolbox;Simulink
DESCRIPTION:
Model an end-to-end monostatic radar using Simulink®. A monostatic radar consists of a transmitter colocated with a receiver. The transmitter generates a pulse which hits the target and produces an echo received by the receiver. By measuring the time location of the echoes, you can estimate the range of the target. The first part of this example demonstrates how to detect the range of a single target using the equivalent of a single element antenna. The second part of the example will show how to build a monostatic radar with a 4-element uniform linear array (ULA) that detects the range of 4 targets.


COMPONENT: phased
EXAMPLENAME: slexSimRFCosimExample
EXAMPLETITLE: Modeling RF Front End in Radar System Simulation
PRODUCT: Phased Array System Toolbox;RF Blockset;Simulink
DESCRIPTION:
In a radar system, the RF front end often plays an important role in defining the system performance. For example, because the RF front end is the first section in the receiver chain, the design of its low noise amplifier is critical to achieving the desired signal to noise ratio (SNR). This example shows how to incorporate RF front end behavior into an existing radar system design.


COMPONENT: phased
EXAMPLENAME: DemoradRadarExample
EXAMPLETITLE: Processing Radar Reflections Acquired with the Demorad Radar Sensor Platform
PRODUCT: MATLAB;Phased Array System Toolbox;Simulink
DESCRIPTION:
Process and visualize FMCW radar echoes acquired via the Demorad Radar Sensor Platform with the Phased Array System Toolbox and Simulink.


COMPONENT: phased
EXAMPLENAME: slexBeamscanMVDRDOAExampleExample
EXAMPLETITLE: Direction of Arrival with Beamscan and MVDR
PRODUCT: Phased Array System Toolbox;Simulink
DESCRIPTION:
Use beamscan and minimum variance distortionless response (MVDR) techniques for direction of arrival (DOA) estimation in Simulink®. It is based on the MATLAB® example Direction of Arrival Estimation with Beamscan, MVDR, and MUSIC.


COMPONENT: phased
EXAMPLENAME: DataflowAudioBeamformingExample
EXAMPLETITLE: Multicore Simulation of Audio Beamforming System
PRODUCT: DSP System Toolbox;MATLAB;Phased Array System Toolbox;Simulink
DESCRIPTION:
How an audio beamforming system simulation model in Simulink® can have improved performance using dataflow domain. It uses the dataflow domain in Simulink to automatically partition the data-driven portions of the communications system into multiple threads and thereby improving the performance of the simulation by executing it on your desktop's multiple cores.


COMPONENT: phased
EXAMPLENAME: slexBistaticExampleExample
EXAMPLETITLE: Simulating a Bistatic Radar with Two Targets
PRODUCT: Phased Array System Toolbox;Simulink
DESCRIPTION:
Simulate a bistatic radar system with two targets. The transmitter and the receiver of a bistatic radar are not co-located and move along different paths.


COMPONENT: phased
EXAMPLENAME: ConvertAzimuthAndElevationToBroadsideAngleExample
EXAMPLETITLE: Convert Azimuth and Elevation to Broadside Angle
PRODUCT: DSP System Toolbox;MATLAB;Phased Array System Toolbox;Signal Processing Toolbox;Simulink
DESCRIPTION:
Convert a direction with an azimuth angle of 45 degrees and an elevation angle of 30 degrees into a broadside angle.


COMPONENT: phased
EXAMPLENAME: RadarSystemVisualExample
EXAMPLETITLE: Simulate and Visualize Range and Doppler Intensity Data in an End-to-end Radar System
PRODUCT: MATLAB;Phased Array System Toolbox;Simulink
DESCRIPTION:
Model an end-to-end radar system and use the scopes to visualize range-intensity and Doppler-intensity data in Simulink.


COMPONENT: phased
EXAMPLENAME: slexMicrophoneBeamformerExampleExample
EXAMPLETITLE: Acoustic Beamforming Using Microphone Arrays
PRODUCT: Phased Array System Toolbox;Simulink
DESCRIPTION:
Beamform signals received by an array of microphones to extract a desired speech signal in a noisy environment. This Simulink® example is based on the MATLAB® example Acoustic Beamforming Using a Microphone Array for System objects.


COMPONENT: phased
EXAMPLENAME: SLHybridBeamformingExample
EXAMPLETITLE: Hybrid MIMO Beamforming with QSHB and HBPS Algorithms
PRODUCT: Communications Toolbox;Phased Array System Toolbox
DESCRIPTION:
Presents a Simulink® model of a multiple input multiple output (MIMO) wireless communication system. The wireless system uses hybrid beamforming technique to improve system throughput.


COMPONENT: phased_dsphdl
EXAMPLENAME: RectangularArrayMVDRBeamformerExample
EXAMPLETITLE: Rectangular Array MVDR Beamformer
PRODUCT:
MATLAB;DSP HDL Toolbox;Fixed-Point Designer;Phased Array System Toolbox;Communications Toolbox;HDL Coder

DESCRIPTION:
Implement a minimum-variance distortionless-response (MVDR) beamformer for a 4x4 rectangular antenna array.


COMPONENT: phased_dsphdl
EXAMPLENAME: FixedPointHDLOptimizedMVDRBeamformerExample
EXAMPLETITLE: FPGA-Based Uniform Linear Array MVDR Beamformer
PRODUCT: MATLAB;Phased Array System Toolbox;Fixed-Point Designer;Simulink
DESCRIPTION:
Implement a fixed-point HDL-optimized minimum-variance distortionless-response (MVDR) beamformer for a uniform linear sensor array (ULA).


COMPONENT: plantdeployment
EXAMPLENAME: GenerateHDLCodeUsingLinearizedSwitchApproximationExample
EXAMPLETITLE: Generate HDL Code for Simscape Models by Using Linearized Switch Approximation
PRODUCT: MATLAB;HDL Coder;Simscape;Simscape Electrical;Simulink
DESCRIPTION:
Generate HDL code and synthesize the results for a three-phase PMSM drive using Linearized Switch Approximation method.


COMPONENT: plantdeployment
EXAMPLENAME: OptimizeHDLImplementationModelSimscapeExample
EXAMPLETITLE: Generate Optimized HDL Implementation Model from Simscape
PRODUCT: MATLAB;HDL Coder;Simscape;Simscape Electrical;Simulink
DESCRIPTION:
Optimize area and timing of HDL implementation model generated from Simscape by using HDL Coder optimizations.


COMPONENT: plantdeployment
EXAMPLENAME: GenerateHDLCodeForSimscapeModelsTrapezoidalSolverExample
EXAMPLETITLE: Generate HDL Code for Simscape Models by Using Trapezoidal Rule Solver
PRODUCT: MATLAB;HDL Coder;Simscape;Simscape Electrical;Simulink Real-Time
DESCRIPTION:
Generate HDL code for a Simscape model by using the Trapezoidal Rule solver and deploy it onto a Speedgoat FPGA I/O module.


COMPONENT: plantdeployment
EXAMPLENAME: DeploySimscapeDCMotorToSpeedgoatFPGAIOModuleExample
EXAMPLETITLE: Deploy Simscape DC Motor Model to Speedgoat FPGA IO Module
PRODUCT: MATLAB;HDL Coder;Simscape;Simscape Electrical;Simulink Real-Time;Simulink Coder
DESCRIPTION:
Generate an FPGA bitstream for a nonlinear Simscape model (DC motor) and deploy it onto a Speedgoat FPGA I/O module.


COMPONENT: plantdeployment
EXAMPLENAME: GenerateHDLCodeSimscapeThreePhasePMSMDriveAveragedSwitchExample
EXAMPLETITLE: Generate HDL Code for Simscape Three-Phase PMSM Drive Containing Averaged Switch
PRODUCT: MATLAB;HDL Coder;Simscape;Simscape Electrical;Simulink
DESCRIPTION:
Generate HDL code and synthesize the results for a three-phase PMSM Simscape models with converter blocks that have averaged switches and deploy onto the FPGAs.


COMPONENT: plantdeployment
EXAMPLENAME: GenerateHDLCodeTwoSpeedTransmissionModelModeChartsExample
EXAMPLETITLE: Generate HDL Code for Two-Speed Transmission Model Containing Mode Charts
PRODUCT: MATLAB;HDL Coder;Simscape Electrical;Simulink;Simscape
DESCRIPTION:
Generate HDL code and synthesize the results for a two-speed transmission model with braking that contains mode charts.


COMPONENT: plccoder
EXAMPLENAME: ModelAndSimulateALadderLogicBasedTemperatureControllerExample
EXAMPLETITLE: Model, Simulate, and Generate Code for a Ladder Logic-Based Temperature Controller
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Model and simulate a ladder logic-based temperature controller of a home. The ladder logic controls the heater based on the thermostat settings and the outside ambient temperature. After verifying that the controller functions for your requirements, generate code for your controller.


COMPONENT: plccoder
EXAMPLENAME: GenerateStructuredTextCodeForWidthBlockExample
EXAMPLETITLE: Generate Structured Text Code for Width Blocks
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
The Width block is commonly used with the For Each subsystem block to compute the signal width inside the for-each loop. This example shows how to generate structured text code for a subsystem that has a Width block.


COMPONENT: plccoder
EXAMPLENAME: GenerateSTCodeByUsingACustomSupportedFunctionListExample
EXAMPLETITLE: Generate Structured Text Code By Using a Custom Supported Function List
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Generate structured text code by using a custom supported function list. Simulink® PLC Coder™ returns an error when generating code for unsupported blocks or functions. Generate structured text code for the unsupported blocks or functions by creating a custom hook file function. You must validate the generated code when using a custom hook file.


COMPONENT: plccoder
EXAMPLENAME: GenerateSTCodeForAMultirateSimulinkSubsystemExample
EXAMPLETITLE: Generate Structured Text Code for a Simulink Subsystem that Has Multirate Components
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Model, simulate, and generate code for a Simulink® subsystem that has components running at different sample times (multirate). Multirate systems are common in industrial applications and programable logic controllers(PLCs). For example, within a PLC there is a task to collect information from sensors to control a process that runs at a slower rate and the actual logic to control the process that runs at a faster rate. To setup your multirate model for simulation and code generation, see Generating Simulink PLC Coder Structured Text Code for Multirate Models.


COMPONENT: plccoder
EXAMPLENAME: GenerateOptimizedSTCodeByFoldingExpressionsExample
EXAMPLETITLE: Generate Optimized Structured Text Code by Folding Expressions
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Generate optimized structured text code by optimizing the output variables of function blocks generated from reusable Simulink® subsystems. Optimize the output variables by using expression folding to minimize the computation of intermediate results at block outputs and the storage of these results in temporary buffers or variables. When you enable the Fold temporary variable using Function block instance output variable optimization, Simulink® PLC Coder™ folds the function block computations into a single expression, instead of generating separate code statements and storage declarations for each function block.


COMPONENT: plccoder
EXAMPLENAME: GenerateSTCodeForVirtualHierarchicalSubsystemsExample
EXAMPLETITLE: Generate Structured Text Code for Hierarchical Simulink Subsystem with Virtual Subsystems
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Generate structured text code for a hierarchical subsystem that contains a virtual subsystem. Use virtual hierarchical subsystems when:


COMPONENT: plccoder
EXAMPLENAME: GenerateStructuredTextCodeFromForEachSubsystemsExample
EXAMPLETITLE: Generate Structured Text Code from For Each Subsystems
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
You can use For Each subsystems to convert inefficient, repetitive algorithms into compact, easy-to-read code. For Each subsystems repeat execution during a simulation time step on each element or subarray of an input signal or mask parameter array.


COMPONENT: plccoder
EXAMPLENAME: SimulateAndGenerateCodeForTimerBasedLadderLogicExample
EXAMPLETITLE: Simulate, Model, and Generate Code for Timer-Based Ladder Logic
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Model and simulate ladder logic for a simple timer-based motor controller. The ladder logic based controller uses an on-delay timer to delay the start of the motor and an off-delay timer to delay the stopping of the motor. After verifying that the controller and timers function for your requirements generate code for the controller.


COMPONENT: plccoder
EXAMPLENAME: GenerateStructuredTextCodeWithVARINOUTVariablesExample
EXAMPLETITLE: Generate Structured Text Code with VAR_IN_OUT Variables
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Model and generate structured text code that has VAR_IN_OUT variables. A VAR_IN_OUT variable is an input and output variable that is a part of the function block interface. Use VAR_IN_OUT variables to pass values to the function block by using the pass by reference method.


COMPONENT: plccoder
EXAMPLENAME: ModelAndSimulateLadderLogicBasedElevatorControllerExample
EXAMPLETITLE: Model, Simulate, and Generate Code for Ladder Logic-Based Elevator Controller
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Rapidly prototype the ladder logic-based controller for a single car elevator by using Simulink® PLC Coder™ to model and simulate the ladder logic. After verifying that the controller works for your requirements, generate code for the controller.


COMPONENT: plccoder
EXAMPLENAME: GenerateStructuredTextCodeForMappedTunableParametersExample
EXAMPLETITLE: Generate Structured Text Code for Interactively Created Tunable Parameters
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Create tunable parameters by using the Simulink® canvas. Generate structured text code that contains the tunable parameters. You create tunable parameters to:


COMPONENT: plccoder
EXAMPLENAME: GenerateSTCodeForHierarchicalSimulinkSubsystemsExample
EXAMPLETITLE: Generate Structured Text Code for Hierarchical Simulink Subsystems
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Generate structured text code for a hierarchical Simulink® subsystem. Use hierarchcail subsystems when:


COMPONENT: plccoder
EXAMPLENAME: ViewRequirementLinksFromGeneratedCodeExample
EXAMPLETITLE: View Requirement Links from Generated Code
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
View requirements linked to a model by using the Requirements Manager app and model object context menu.


COMPONENT: plccoder
EXAMPLENAME: GenerateSTCodeForSimulinkModelWithFixedPointDataTypesExample
EXAMPLETITLE: Generate Structured Text Code for Simulink Model That Has Fixed-Point Data Types
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Generate structured text code for a Simulink® model that has fixed-point data types by using Simulink® PLC Coder™.


COMPONENT: plccoder
EXAMPLENAME: RunTimeDataCollectionByUsingExternalModeLoggingExample
EXAMPLETITLE: Run-Time Data Collection by Using External Mode Logging
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Generate code by using external mode logging. Download the generated code with the external mode logging function to the target Programmable Logic Controller (PLC) and collect run-time data. Visualize and monitor the collected run-time data by using Simulation Data Inspector and an Open Platform Communications (OPC) server.


COMPONENT: plccoder
EXAMPLENAME: GenerateStructuredTextCodeForVarialbleSizeSignalsExample
EXAMPLETITLE: Generate Structured Text Code for Variable-Size Signals
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Deploy applications such as machine learning models to your target PLC by generating code for variable-size signals. Verify the generated structured text code by generating test bench code and importing the generated test bench code into your target IDE.


COMPONENT: plccoder
EXAMPLENAME: SimulationAndCodeGenerationForTunableParametersExample
EXAMPLETITLE: Generate Structured Text Code for Programmatically Created Tunable Parameters
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Programmaticaly create tunable parameters and generate structured text code. You create tunable parameters to:


COMPONENT: plccoder
EXAMPLENAME: GenerateSTCodeForAStateflowChartWithAbsTimeTemporalLogicExample
EXAMPLETITLE: Generate Structured Text Code for a Stateflow Chart That Uses Absolute-Time Temporal Logic
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Model, simulate, and generate code for a Stateflow® chart that uses absolute-time temporal logic. Absolute-time temporal logic tracks elapsed time since the state became active. Absolute-time temporal logic is used in industrial applications on programmable logic controllers (PLCs) to implement logic for processes that transition between process steps by using a combination of logic-and time-based transitions. After verifying that the model functions for your requirements, generate code for the Stateflow® chart by using Simulink® PLC Coder™.


COMPONENT: plccoder
EXAMPLENAME: IntegrateUserDefinedFBsDataTypesAndGlobalVarsIntoSTExample
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
EXAMPLETITLE:
Integrate User-Defined Function Blocks, Data Types, and Global Variables into Generated Structured Text

DESCRIPTION:
Integrate user-defined function blocks, data types, and global variables into generated structured text. You can integrate user-defined function blocks, data types, and global variables into your structured text code by creating blocks, data types, and variables in Simulink® and excluding them from the code generation. You can then add your user-generated code into the empty definitions. You can use this technique to customize your model to meet specific requirements.


COMPONENT: plccoder
EXAMPLENAME: SimulationAndStructuredTextGenerationForMPCControllerExample
EXAMPLETITLE: Simulation and Structured Text Generation for MPC Controller Block
PRODUCT: MATLAB;Simulink PLC Coder;Model Predictive Control Toolbox;Simulink
DESCRIPTION:
Simulate and generate structured text for an MPC Controller block by using Simulink® PLC Coder™ software. The generated code uses single-precision data.


COMPONENT: plccoder
EXAMPLENAME: SimulateAndGenerateStructuredTextCodeForAStateflowRChartExample
EXAMPLETITLE: Simulate and Generate Structured Text Code for a Stateflow Chart
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Simulate and generate code for the ControlModule Stateflow® chart from the plcdemo_stateflow_controller model.


COMPONENT: plccoder
EXAMPLENAME: SimulateAndGenerateSTCodeForRockwellMotionInstructionsExample
EXAMPLETITLE: Simulate and Generate Structured Text Code for Rockwell Automation Motion Instructions
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Model Rockwell Automation® motion instructions in Stateflow®. Generate structured text code for the modeled motion instructions by using Simulink® PLC Coder™.


COMPONENT: plccoder
EXAMPLENAME: IncludePortsAndBusElementDescriptionsInGeneratedCodeExample
EXAMPLETITLE: Add Subsystem Port and Bus Descriptions in Generated Code
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Add descriptions for subsystem input ports, output ports, and buses. The generated structured text code then includes these port and bus descriptions.


COMPONENT: plccoder
EXAMPLENAME: SpeedCruiseControlSystemUsingSimulinkRAndStateflowRExample
EXAMPLETITLE: Simulate and Generate Code for Speed Cruise Control System
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Simulate and generate code for a speed cruise control system. The cruise control system is modeled using Simulink® and Stateflow®.


COMPONENT: plccoder
EXAMPLENAME: GenerateStructuredTextCodeForAMATLABFunctionBlockExample
EXAMPLETITLE: Generate Structured Text Code for a MATLAB Function Block
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Model, simulate, and generate code for a Simulink® subsystem that has a MATLAB® Function Block. Generate code for the MATLAB Function Block by using Simulink PLC Coder™.


COMPONENT: plccoder
EXAMPLENAME: ImportL5XLadderDiagramFilesIntoSimulinkExample
EXAMPLETITLE: Import L5X Ladder Diagram Files into Simulink
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Simulate, test, and validate your .L5X ladder diagram files by importing your ladder diagram files into Simulink®. Use the plcimportladder function to import your ladder diagram files into Simulink. Simulink PLC Coder™ supports only import of ladder diagram files created by using Rockwell Automation® RSLogix 5000® and Studio 5000 ® integrated development environments (IDEs).


COMPONENT: plccoder
EXAMPLENAME: VariableStepSpeedCruiseControlSystemExample
EXAMPLETITLE: Variable Step Speed Cruise Control System
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Simulate and generate code for the Controller subsystem from a speed cruise control model by using variable continuous step solver.


COMPONENT: plccoder
EXAMPLENAME: GenerateBusVariablesAsStructuresInStructuredTextCodeExample
EXAMPLETITLE: Generate Bus Variables as STRUCT Data Types in Structured Text Code
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Use Simulink® PLC Coder™ to generate bus variables as STRUCT data types in the generated structured text. To generate bus variables as STRUCT data types in the generated code, you must model your buses as nonvirtual buses. To create a nonvirtual bus, see Create Nonvirtual Buses. Simulink® PLC Coder™ does not support the generation of STRUCT data types from virtual buses.


COMPONENT: plccoder
EXAMPLENAME: VerifyGeneratedCodeByUsingCosimulationExample
EXAMPLETITLE: Verify Generated Code by Using Cosimulation
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Verify your generated code by using cosimulation. The generated code and testbench run on a Codesys software-based programable logic controller (soft PLC). The Simulink ™ model uses Open Platform Communication Unified Architecture (OPC UA) to communicate with and retrieve the cosimulated data from the soft PLC. The Simulink model verifies the generated code by comparing the model simulation results to the cosimulated soft PLC results.


COMPONENT: plccoder
EXAMPLENAME: GenerateStructuredTextCodeForReusableSubsystemsExample
EXAMPLETITLE: Generate Structured Text Code for Reusable Subsystems
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Simulate and generate structured text code for an atomic reusable subsystem. Reusable subsystems enable you to model commonly used blocks as a subsystem and reuse the subsystems multiple times within a model. Use reusable subsystems in your model to :


COMPONENT: plccoder
EXAMPLENAME: ModelAndGenerateCodeForJMPandLBLadderDiagramInstructionsExample
EXAMPLETITLE: Model and Generate Code for Jump and Label Ladder Diagram Instructions
PRODUCT: MATLAB;Simulink PLC Coder;Simulink
DESCRIPTION:
Model a ladder diagram in Simulink® that uses the JMP and LBL instructions. Simulate the ladder diagram to verify its behavior and generate ladder diagram code from the model. The JMP and LBL instructions branch and loop the ladder diagram code.


COMPONENT: plutoradio
EXAMPLENAME: QPSKTransmitterWithADALMPLUTORadioSimulinkExample
EXAMPLETITLE: QPSK Transmitter with ADALM-PLUTO Radio in Simulink
PRODUCT: MATLAB;Simulink
DESCRIPTION:
How to use the ADALM-PLUTO Radio with Simulink® to implement a QPSK transmitter. The ADALM-PLUTO Radio in this model will keep transmitting indexed 'Hello world' messages at its specified center frequency. You can demodulate the transmitted message using the QPSK Receiver with ADALM-PLUTO Radio model. This example assumes that two ADALM-PLUTO Radios are attached to your computer.


COMPONENT: plutoradio
EXAMPLENAME: QPSKReceiverWithADALMPLUTORadioSimulinkExample
EXAMPLETITLE: QPSK Receiver with ADALM-PLUTO Radio in Simulink
PRODUCT: MATLAB;Simulink
DESCRIPTION:
How to use the the ADALM-PLUTO Radio with Simulink® to implement a QPSK receiver. The receiver addresses practical issues in wireless communications, e.g. carrier frequency and phase offset, timing offset and frame synchronization. This model receives the signal sent by the QPSK Transmitter with ADALM-PLUTO Radio model. The receiver demodulates the received symbols and outputs a simple message to the MATLAB® command line.


COMPONENT: plutoradio
EXAMPLENAME: FrequencyCorrectionForADALMPLUTORadioInSimulinkExample
EXAMPLETITLE: Frequency Correction for ADALM-PLUTO Radio in Simulink
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Synchronize both the baseband sample rate and the center frequency of two PlutoSDRs by using the Frequency correction parameter of the ADALM-PLUTO Radio Receiver block.


COMPONENT: plutoradio
EXAMPLENAME: FrequencyOffsetCalibrationWithADALMPLUTORadioSimulinkExample
EXAMPLETITLE: Frequency Offset Calibration with ADALM-PLUTO Radio in Simulink
PRODUCT: MATLAB;Simulink
DESCRIPTION:
These two models show how to determine the relative frequency offset between two ADALM-PLUTO radios.


COMPONENT: predmaint
EXAMPLENAME: CentrifugalPumpFaultDiagnosisUsingResidualAnalysisExample
EXAMPLETITLE: Fault Diagnosis of Centrifugal Pumps Using Residual Analysis
PRODUCT:
Control System Toolbox;MATLAB;Simulink;Statistics and Machine Learning Toolbox;System Identification Toolbox

DESCRIPTION:
Use a model parity-equations-based approach for detection and diagnosis of faults in a pumping system.


COMPONENT: predmaint
EXAMPLENAME: GenerateEnsembleOfFaultDataExample
EXAMPLETITLE: Generate Ensemble of Fault Data
PRODUCT: MATLAB;Predictive Maintenance Toolbox;Simscape;Simulink
DESCRIPTION:
Generate a simulation ensemble datastore of data representing a machine operating under fault conditions by simulating a Simulink® model of the machine while varying a fault parameter.


COMPONENT: predmaint
EXAMPLENAME: GenerateAndUseSimulatedDataEnsembleExample
EXAMPLETITLE: Generate and Use Simulated Data Ensemble
PRODUCT: MATLAB;Predictive Maintenance Toolbox;Simscape;Simulink
DESCRIPTION:
If you have a Simulink model of your system under fault conditions, you can generate an ensemble of simulated data for developing predictive-maintenance algorithms.


COMPONENT: predmaint
EXAMPLENAME: UsingSimulinkToGenerateFaultDataExample
EXAMPLETITLE: Using Simulink to Generate Fault Data
PRODUCT: MATLAB;Predictive Maintenance Toolbox;Simscape;Simulink
DESCRIPTION:
Use a Simulink model to generate fault and healthy data, and use the data to develop a condition monitoring algorithm.


COMPONENT: predmaint
EXAMPLENAME: DCLinkCapacitorLifeEstimationExample
EXAMPLETITLE: Remaining Useful Life Estimation of a DC-link Capacitor in a Power Converter
PRODUCT: MATLAB;Predictive Maintenance Toolbox;Simscape;Simulink;Simscape Electrical
DESCRIPTION:
Design and Implement a remaining useful life (RUL) estimation algorithm for an aluminum electrolytic DC-link capacitor in an AC-DC-AC power converter system.


COMPONENT: predmaint
EXAMPLENAME: MultiClassFaultDetectionUsingSimDataExample
EXAMPLETITLE: Multi-Class Fault Detection Using Simulated Data
PRODUCT:
MATLAB;Predictive Maintenance Toolbox;Simscape;Simscape Electrical;Simscape Fluids;Simscape Multibody;Simulink

DESCRIPTION:
Use a Simulink model to generate faulty and healthy data, and use the data to develop a multi-class classifier to detect different combinations of faults.


COMPONENT: radar
EXAMPLENAME: RadarArchitecturePart1Example
EXAMPLETITLE: Radar Architecture: System Components and Requirements Allocation (Part 1)
PRODUCT: MATLAB;Radar Toolbox
DESCRIPTION:
Starting from a set of performance requirements, design, implement, and test a radar system in Simulink .


COMPONENT: radar
EXAMPLENAME: FrequencyAgilitySLExample
EXAMPLETITLE: Interference Mitigation Using Frequency Agility Techniques
PRODUCT: Radar Toolbox;Simulink
DESCRIPTION:
Model frequency agility techniques to counter the effects of interference in radar, communications, and EW systems.


COMPONENT: radar
EXAMPLENAME: slexSTAPExampleExample
EXAMPLETITLE: Clutter and Jammer Mitigation with STAP
PRODUCT: Radar Toolbox;Simulink
DESCRIPTION:
Use Simulink® to suppress clutter and jammer interference from received pulses of a monostatic radar.


COMPONENT: raspberrypi
EXAMPLENAME: ChromaKeyingMATLABFunctionBlockRaspberryPiExample
EXAMPLETITLE: Customize Color Within Video Using Raspberry Pi
PRODUCT: MATLAB;Image Processing Toolbox
DESCRIPTION:
Replace a particular color in a live video stream with an image on Raspberry Pi® hardware by using a MATLAB Function block.


COMPONENT: raspberrypi
EXAMPLENAME: MODBUSTCPIPCommMasterSlaveDevicesUsingRaspberryPiExample
EXAMPLETITLE: MODBUS TCP/IP Communication Between Client and Server Devices Using Raspberry Pi Hardware
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to implement MODBUS® TCP/IP communication between MODBUS client and server devices. It also shows how to communicate between the two devices in four modes of operation, Client Read, Client Write, Server Read, and Server Write.


COMPONENT: raspberrypi
EXAMPLENAME: ClassifyObjectsDeepLearningRaspberryPiHardwareExample
EXAMPLETITLE: Classify Objects Using Deep Learning Algorithm on Raspberry Pi Hardware
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to deploy a deep learning algorithm that classifies objects using the ResNet-50 convolutional neural network. This pretrained network is 50 layers deep and can classify images into 1000 object categories, such as keyboard, mouse, pencil, and many more. You can experiment with different objects in your surroundings to see how accurately the network classifies images on the Raspberry Pi hardware.


COMPONENT: raspberrypi
EXAMPLENAME: AutorotateAnImageDisplayedOnSenseHATLEDMatrixExample
EXAMPLETITLE: Auto-Rotate Image Displayed on Raspberry Pi Sense HAT LED Matrix
PRODUCT: MATLAB
DESCRIPTION:
Develop a Simulink® model to implement an algorithm to read the Accelerometer On-board Sense HAT and control the rotation of the image displayed on the LED matrix.


COMPONENT: raspberrypi
EXAMPLENAME: GetStartedDeployWebBasedCustomizableDashboardBlocksRaspiExample
EXAMPLETITLE: Get Started with Deploying Web-Based Customizable Dashboard Blocks on Raspberry Pi
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to create an interactive dashboard display using the Dashboard Circular Gauge and Knob blocks from the Simulink Customizable Blocks library. The example also shows you how to deploy the interactive dashboard on your Raspberry Pi hardware board. You can customize the visual aspects of the dashboard widgets so that the dashboard looks like a real system. You can obtain the what you see is what you get (WYSIWYG) visualization on a web browser or a display connected to the Raspberry Pi hardware.


COMPONENT: raspberrypi
EXAMPLENAME: ReceiveLidarLaserScanDataOverROSFromRaspberryPiExample
EXAMPLETITLE: Read Lidar Laser Scan Data over ROS from Raspberry Pi
PRODUCT: MATLAB;ROS Toolbox
DESCRIPTION:
Use Simulink® Support Package for Raspberry Pi® Hardware to read and receive a 2-D lidar scan data of an indoor environment from a ROS network using the Raspberry Pi hardware board.


COMPONENT: raspberrypi
EXAMPLENAME: ReadWriteThingSpeakChannelRaspberryPiHTTPClientExample
EXAMPLETITLE: Read and Write to ThingSpeak Channel Using Raspberry Pi HTTP Client Block
PRODUCT: MATLAB
DESCRIPTION:
Use Simulink® Support Package for Raspberry Pi® Hardware to read and write data to a field in a ThingSpeak™ channel. In this example, you read data from the GPIO pin of the Raspberry Pi hardware and write it to a field in a ThingSpeak channel.


COMPONENT: raspberrypi
EXAMPLENAME: WorkingWithRaspberryPiCANBlocksExample
EXAMPLETITLE: Transmit and Receive Data Using Raspberry Pi CAN Blocks
PRODUCT: MATLAB
DESCRIPTION:
To use Simulink® Support Package for Raspberry Pi® Hardware to transmit and receive data from the CAN network using the specified CAN device.


COMPONENT: raspberrypi
EXAMPLENAME: SpatializeAudioSignalUsingMatlabFunctionRaspberrypiExample
EXAMPLETITLE: Spatialize Monaural Audio into 5.1 Channel Surround Sound Using Raspberry Pi
PRODUCT: Audio Toolbox;MATLAB
DESCRIPTION:
Spatialize a monaural audio signal into a 5.1 channel surround sound on Raspberry Pi® hardware by using a MATLAB Function block with the Simulink® Support Package for Raspberry Pi Hardware.


COMPONENT: raspberrypi
EXAMPLENAME: TriggerFunctionCallRaspberryPiSingleTapBMI160SensorExample
PRODUCT: MATLAB
EXAMPLETITLE:
Trigger Downstream Function-Call Subsystem Using Raspberry Pi External Interrupt Block with Single Tap Event on BMI160 Sensor

DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to trigger a downstream function-call in Monitor and Tune action when single tap event occurs on the BMI160 sensor using a Raspberry Pi External Interrupt block. This example model for monitor and tune simulation showcases the capabilities of the External Interrupt block during a single tap event on the BMI160 sensor.


COMPONENT: raspberrypi
EXAMPLENAME: ImageInversionExample
EXAMPLETITLE: Implement Image Inversion Algorithm Using Raspberry Pi
PRODUCT: MATLAB
DESCRIPTION:
Use the V4L2 Video Capture and the SDL Video Display blocks from the Raspberry Pi® block library to implement an image inversion algorithm with a Simulink® model, and to run the model on Raspberry Pi hardware.


COMPONENT: raspberrypi
EXAMPLENAME: ControllingLEGOEV3RobotUsingRaspPiSenseHATExample
EXAMPLETITLE: Control LEGO MINDSTORMS EV3 Robot Using Raspberry Pi Sense HAT
PRODUCT: MATLAB
DESCRIPTION:
Read the Accelerometer on Raspberry Pi® Sense HAT and use this data to control the motion of a LEGO® MINDSTORMS® EV3 robot.


COMPONENT: raspberrypi
EXAMPLENAME: GetStartedMotorDrivesRoboticsAppRaspberryPiSimulinkExample
EXAMPLETITLE: Get Started with Motor Drives for Robotics Applications Using Raspberry Pi and Simulink
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware and a Raspberry Pi hardware board to drive motors.


COMPONENT: raspberrypi
EXAMPLENAME: VerifyFIRFilterRaspberryPiExample
EXAMPLETITLE: Verify FIR Filter on Raspberry Pi Hardware
PRODUCT: MATLAB;Embedded Coder;DSP System Toolbox
DESCRIPTION:
Use the Code Replacement Library (CRL) for Raspberry Pi® hardware with DSP blocks. The model uses the FIR filter block to filter two sine waves of different frequencies.


COMPONENT: raspberrypi
EXAMPLENAME: RecognizeHandDigitsMNISTDataSetRaspberryPiExample
EXAMPLETITLE: Recognize Handwritten Digits Zero to Nine Using MNIST Data Set on Raspberry Pi Hardware
PRODUCT: MATLAB;Computer Vision Toolbox;Statistics and Machine Learning Toolbox
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to recognize images of handwritten digits from zero to nine. In this example, a web camera interfaced with a Raspberry Pi hardware board is used to capture images of the handwritten numbers. The algorithm recognizes the digits and then outputs a label for the digit along with its prediction probability.


COMPONENT: raspberrypi
EXAMPLENAME: ConfigureCalibratePanTiltHardwareUsingRaspPiPanTiltHATExample
EXAMPLETITLE: Configure and Calibrate Pan Tilt Hardware Using Raspberry Pi Pan Tilt HAT
PRODUCT: MATLAB
DESCRIPTION:
Configure and calibrate the pan and tilt hardware using the Pan Tilt HAT block from Simulink® Support Package for Raspberry Pi® Hardware.


COMPONENT: raspberrypi
EXAMPLENAME: GetStartedSensorsRoboticsAppRaspberryPiSimulinkOnlineExample
EXAMPLETITLE: Get Started with Sensors for Robotics Applications Using Raspberry Pi and Simulink Online
PRODUCT: MATLAB
DESCRIPTION:
Use Simulink® Support Package for Raspberry Pi® Hardware and a Raspberry Pi hardware board to get started with the driver blocks for commonly used robotics sensors.


COMPONENT: raspberrypi
EXAMPLENAME: ConfigureImageDevicePropRaspiV4L2BlockObjectDetectionExample
EXAMPLETITLE: Configure Image and Device Properties of Raspberry Pi V4L2 Video Capture Block to Detect Objects
PRODUCT: MATLAB;Computer Vision Toolbox
DESCRIPTION:
Configure the image and device properties of the V4L2 Video Capture block from Simulink® Support Package for Raspberry Pi® Hardware and observe the output in the SDL Video Display block. This example also shows how to tune the image properties of the V4L2 Video Capture block to detect objects in a noisy and distorted real-time video.


COMPONENT: raspberrypi
EXAMPLENAME: PredictMonitorVibrationMovingObjectMLAlgoRaspberryPiExample
EXAMPLETITLE: Perform Predictive Maintenance for Rotating Device Using Machine Learning Algorithm on Raspberry Pi
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;DSP System Toolbox
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to predict and monitor the health of a rotating device using a machine learning algorithm. You can use this example for predictive maintenance of any rotating device or piece of equipment so that you can fix them before they fail.


COMPONENT: raspberrypi
EXAMPLENAME: StreamVideoNetworkRaspiVideoStreamTransmitBlockExample
EXAMPLETITLE: Stream Video Over Network Using Raspberry Pi Video Stream Transmit Block
PRODUCT: MATLAB;Computer Vision Toolbox
DESCRIPTION:
Use the Video Stream Transmit block from the Simulink Support Package for Raspberry Pi Hardware to stream a live video over a network using real-time streaming protocol (RTSP).


COMPONENT: raspberrypi
EXAMPLENAME: ImplementConnectedIOPublishDataWebsocketserverExample
EXAMPLETITLE: Implement Connected I/O on Raspberry Pi Hardware and Publish Data to WebSocket Server
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to develop an image processing system on Raspberry Pi board using a camera in the connected I/O mode. The example also shows you how to publish the output on a web browser and on a SDL video display screen.


COMPONENT: raspberrypi
EXAMPLENAME: StreamImagesFromRaspberryPiUsingRobotOperatingSystemROSExample
EXAMPLETITLE: Stream Images from Raspberry Pi Using Robot Operating System
PRODUCT: MATLAB;Computer Vision Toolbox;ROS Toolbox
DESCRIPTION:
Stream images captured from a webcam on a Raspberry Pi® board to the host computer using a ROS communication interface. In this example, you stream images from your Raspberry Pi board to your host computer using the ROS Publish blocks. You use the ROS MATLAB® command line interface to display the images on your host computer.


COMPONENT: raspberrypi
EXAMPLENAME: PublishAndSubscribeToMessagesUsingMQTTBlocksExample
EXAMPLETITLE: Publish and Subscribe to Messages on ThingSpeak Using MQTT Blocks on Raspberry Pi
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to publish a message to a topic from Raspberry Pi in the ThingSpeak™ MQTT broker. This example also shows how to subscribe to a topic and receive a message from the ThingSpeak MQTT broker to Raspberry Pi. For more information on MQTT protocol, see MQTT Basics (ThingSpeak) and Publish MQTT Messages and Subscribe to Message Topics. In this example, ThingSpeak is the MQTT broker and Raspberry Pi board is the MQTT client (publisher and subscriber).


COMPONENT: raspberrypi
EXAMPLENAME: ParametricAudioEqualizerExample
EXAMPLETITLE: Implement Parametric Audio Equalizer Using Raspberry Pi
PRODUCT: MATLAB;DSP System Toolbox
DESCRIPTION:
Use ALSA Audio Playback block from the Raspberry Pi® block library to implement a parametric audio equalizer algorithm with a Simulink® model and to run the model on Raspberry Pi hardware.


COMPONENT: raspberrypi
EXAMPLENAME: TriggerFunctionCallRaspberryPiExternalInterruptExample
EXAMPLETITLE: Trigger Downstream Function-Call Subsystem Using Raspberry Pi External Interrupt Block
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to trigger a downstream function-call in the connected IO mode and external mode of simulation (Monitor and Tune) using a Raspberry Pi External Interrupt block. This example provides two Simulink models, one each for connected IO mode and external mode of simulation, to show the capabilities of the External Interrupt block in each of the modes.


COMPONENT: raspberrypi
EXAMPLENAME: DetectAndTrackFaceUsingRaspberryPiPanTiltHATExample
EXAMPLETITLE: Detect and Track Face Using Raspberry Pi Pan Tilt HAT
PRODUCT: MATLAB;Computer Vision Toolbox
DESCRIPTION:
Use the Pan Tilt HAT block from Simulink® Support Package for Raspberry Pi® Hardware to detect and track a face in a video frame. The example also tracks a face when a person tilts their head either left or right or moves toward or away from the camera. If the face is not visible or goes out of focus, the model tries to reacquire the face and then tracks the face. The model in this example can detect and track only one face at a time. You can also enable the proportional-integral-derivative (PID) controller to achieve a smooth motion of the pan and tilt hardware module for tracking the face.


COMPONENT: raspberrypi
EXAMPLENAME: EstimateDirectionArrivalLinearArrayMicRaspberryPiExample
EXAMPLETITLE: Estimate Direction of Arrival with Linear Array of Microphones Using Raspberry Pi
PRODUCT: MATLAB;DSP System Toolbox;Audio Toolbox
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to estimate the Direction of Arrival (DOA) of a sound source using multiple microphone pairs within a linear array using the Raspberry Pi hardware board. A servo motor is used to point towards the sound source based on the estimated DOA.


COMPONENT: raspberrypi
EXAMPLENAME: ImplementBandPassFilterRaspberryPiExample
EXAMPLETITLE: Implement Bandpass Filter on Raspberry Pi
PRODUCT: MATLAB;DSP System Toolbox;Audio Toolbox
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to design a bandpass filter using DSP System Toolbox™.


COMPONENT: raspberrypi
EXAMPLENAME: PublishDataRaspberryPiSenseHATWebsocketServerExample
EXAMPLETITLE: Publish Data from Raspberry Pi Sense HAT to WebSocket Server
PRODUCT: MATLAB;DSP System Toolbox
DESCRIPTION:
Use Simulink® Support Package for Raspberry Pi® Hardware to publish the signals obtained from a Raspberry Pi Sense HAT to a WebSocket server, and read the data on a web browser in the WebSocket client.


COMPONENT: raspberrypi
EXAMPLENAME: TrackObjectUsingROSAndSimulinkOnRaspberryPiExample
EXAMPLETITLE: Track Object Using ROS and Simulink on Raspberry Pi
PRODUCT: MATLAB;Computer Vision Toolbox;ROS Toolbox
DESCRIPTION:
Use Simulink® Support Package for Raspberry Pi® Hardware, ROS Toolbox, and a Raspberry Pi hardware board to track a green colored object. This example also shows how to use the Publish and Subscribe blocks to establish communication between the ROS node deployed on the Raspberry Pi hardware board and the ROS node in Simulink (host computer).


COMPONENT: raspberrypi
EXAMPLENAME: ControlColorOfLEDMatrixOnRaspberryPiSenseHATWebSocketsExample
EXAMPLETITLE: Control Color of LED Matrix on Raspberry Pi Sense HAT over WebSockets
PRODUCT: MATLAB;DSP System Toolbox
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to control the color of an 8x8 LED matrix on Raspberry Pi Sense HAT from a web page over WebSockets.


COMPONENT: raspberrypi
EXAMPLENAME: DetectStopSignalTrafficSignRaspberryPiSimulinkExample
EXAMPLETITLE: Detect Stop Signal Traffic Sign Using Raspberry Pi and Simulink
PRODUCT: MATLAB;Computer Vision Toolbox
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to detect a stop signal traffic sign. The example uses a cascade object detector to detect a stop sign using the Viola-Jones algorithm.


COMPONENT: raspberrypi
EXAMPLENAME: DevelopObstacleDetectionRobotToFSensorRaspberryPiExample
EXAMPLETITLE: Develop Obstacle Detection Robot Using ToF Sensor with Raspberry Pi
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to interface a VL53L0X Time of Flight (ToF) sensor with the Raspberry Pi hardware to develop an obstacle detection robot.


COMPONENT: raspberrypi
EXAMPLENAME: GettingStartedWithSimulinkRaspberryPiHardwareExample
EXAMPLETITLE: Get Started with Simulink Support Package for Raspberry Pi Hardware
PRODUCT: MATLAB
DESCRIPTION:
Use Simulink® Support Package for Raspberry Pi® Hardware to run a Simulink model on Raspberry Pi hardware.


COMPONENT: raspberrypi
EXAMPLENAME: MonitoringEngineRPMUsingRaspberryPiCANBlocksExample
EXAMPLETITLE: Monitor Engine RPM Using Raspberry Pi CAN Blocks
PRODUCT: MATLAB
DESCRIPTION:
Use Simulink® Support Package for Raspberry Pi® Hardware to monitor vehicle engine RPM and read the data on a web browser.


COMPONENT: raspberrypi
EXAMPLENAME: DeployAPitchShiftAlgorithmRaspberryPiHardwareExample
EXAMPLETITLE: Shift Pitch of Audio Signal Using Raspberry Pi
PRODUCT: Audio Toolbox;MATLAB
DESCRIPTION:
Shift the pitch of an audio signal on Raspberry Pi® hardware by using a MATLAB Function block with the Simulink® Support Package for Raspberry Pi Hardware.


COMPONENT: raspberrypi
EXAMPLENAME: VideoMosaickingUsingRapsberryPiPanTiltHATExample
EXAMPLETITLE: Video Mosaicking Using Raspberry Pi Pan Tilt HAT
PRODUCT: MATLAB;Computer Vision Toolbox;Signal Processing Toolbox
DESCRIPTION:
Use the Pan Tilt HAT block from Simulink® Support Package for Raspberry Pi® Hardware to create a mosaic from a video sequence. Video mosaicking is the process of stitching video frames together to form a comprehensive view of a scene. The resulting mosaic image is a compact representation of the video data. This technique is often used in video compression and surveillance applications.


COMPONENT: raspberrypi
EXAMPLENAME: CountingStepsUsingRaspberryPiSenseHATExample
EXAMPLETITLE: Count Steps Using Raspberry Pi Sense HAT
PRODUCT: MATLAB;Simulink Coder
DESCRIPTION:
Demonstrates an application that counts the number of steps a person walked while holding a Raspberry Pi® Sense HAT.


COMPONENT: raspberrypi
EXAMPLENAME: GettingStartedWithRobotOperatingSystemROSOnRaspberryPiRExample
EXAMPLETITLE: Get Started with Robot Operating System on Raspberry Pi
PRODUCT: MATLAB;ROS Toolbox
DESCRIPTION:
Build a standalone robot operating system (ROS) node from a Simulink® model on a Raspberry Pi® hardware board.


COMPONENT: raspberrypi
EXAMPLENAME: DeployEdgeDetectionOnRaspberryPiExample
EXAMPLETITLE: Detect Boundaries of Objects Within Video Using Raspberry Pi
PRODUCT: MATLAB
DESCRIPTION:
Identify the boundaries of objects in a live video stream on Raspberry Pi® hardware by using a MATLAB Function block with the Simulink® Support Package for Raspberry Pi Hardware. The process of identifying boundaries of objects is known as edge detection. This example implements the Sobel edge detection algorithm to identify the boundaries of the objects.


COMPONENT: raspberrypi
EXAMPLENAME: ReadTemperatureFromATMP102SensorExample
EXAMPLETITLE: Read Temperature from TMP102 Sensor Using Raspberry Pi
PRODUCT: MATLAB
DESCRIPTION:
Illustrates how to use Simulink® Support Package for Raspberry Pi® Hardware to configure and read temperature from a TMP102 sensor.


COMPONENT: raspberrypi
EXAMPLENAME: ControlLEDStatusUsingThingSpeakTalkBackOnRaspberryPiExample
EXAMPLETITLE: Control LED Status Using ThingSpeak TalkBack on Raspberry Pi
PRODUCT: MATLAB
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to fetch and execute commands from a ThingSpeak™ TalkBack queue and use them to change the status of an LED onboard a Raspberry Pi hardware board.


COMPONENT: raspberrypi
EXAMPLENAME: ImplementAdaptiveFilterNoiseCancellationRaspberryPiExample
EXAMPLETITLE: Implement Adaptive Filter for Noise Cancellation Using Raspberry Pi
PRODUCT: MATLAB;DSP System Toolbox;Audio Toolbox
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to implement an adaptive filter for noise cancellation using DSP System Toolbox™.


COMPONENT: raspberrypi
EXAMPLENAME: DevelopRobotNavigationSystemRaspberryPiSimulinkExample
EXAMPLETITLE: Develop Robot Navigation System Using Raspberry Pi and Simulink
PRODUCT: MATLAB;Computer Vision Toolbox
DESCRIPTION:
Illustrates how to use the Simulink® Support Package for Raspberry Pi® Hardware to develop a robot navigation system.


COMPONENT: raspberrypi
EXAMPLENAME: GetStartedAudioSignalProcessingRaspberryPiExample
EXAMPLETITLE: Get Started with Audio Signal Processing Using Raspberry Pi
PRODUCT: MATLAB;DSP System Toolbox;Audio Toolbox
DESCRIPTION:
Use the Simulink® Support Package for Raspberry Pi® Hardware to get started with audio signal processing applications on the Raspberry Pi hardware. It also shows how to:


COMPONENT: raspberrypi
EXAMPLENAME: AudioVisualizerUsingRaspberryPiTMSenseHATExample
EXAMPLETITLE: Simulate Audio Visualizer on Raspberry Pi Sense HAT
PRODUCT: MATLAB;DSP System Toolbox
DESCRIPTION:
Simulate an audio visualizer on Sense HAT using the Simulink® Support Package for Raspberry Pi® Hardware.


COMPONENT: raspberrypi
EXAMPLENAME: LogHumidityTempDatabaseCalcDewPtExternalCCodeIntegExample
PRODUCT: MATLAB;Database Toolbox
EXAMPLETITLE:
Log Humidity and Temperature Values to Database and Calculate Dew Point Using External C Code Integration Workflow

DESCRIPTION:
Use Simulink® Support Package for Raspberry Pi® Hardware to integrate a user-defined C function with a Simulink model and achieve the following:


COMPONENT: raspberrypi
EXAMPLENAME: NE10CCodeRaspberrypiFIRFilterMATLABExample
EXAMPLETITLE: Support NE10 Library C Code Generation of dsp.FIRFilter in MATLAB Function Block
PRODUCT: MATLAB;Embedded Coder;DSP System Toolbox
DESCRIPTION:
Use the Code Replacement Library (CRL) for Raspberry Pi® hardware with DSP System object™. The model uses a MATLAB Function that contains a dsp.FIRFilter System object to filter two sine waves of different frequencies.


COMPONENT: raspberrypiio
EXAMPLENAME: ControlAndMonitorSenseHATAndroidRaspiExample
EXAMPLETITLE: Transfer Data over TCP/IP Between Raspberry Pi Sense HAT and Android Device
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Use MATLAB® commands to send data over TCP/IP from Raspberry Pi® Sense HAT to an Android™ device and also receive RGB color values from the Android device and display the same on the LED matrix of Sense HAT.


COMPONENT: rl
EXAMPLENAME: CreateASimulinkEnvironmentForMultipleAgentsExample
EXAMPLETITLE: Create Simulink Environment for Multiple Agents
PRODUCT: MATLAB;Reinforcement Learning Toolbox
DESCRIPTION:
Create an environment for the Simulink model from the example Train Multiple Agents to Perform Collaborative Task.


COMPONENT: rl
EXAMPLENAME: ActionAndObsInfoFromReinforcementLearningEnvironmentExample
EXAMPLETITLE: Extract Action and Observation Specifications from Reinforcement Learning Environment
PRODUCT: MATLAB;Reinforcement Learning Toolbox
DESCRIPTION:
The reinforcement learning environment for this example is a longitudinal dynamics model comprising two cars, a leader and a follower. The vehicle model is also used in the Adaptive Cruise Control System Using Model Predictive Control example.


COMPONENT: rl
EXAMPLENAME: AutomaticParkingValetWithUnrealEngineSimulationExample
EXAMPLETITLE: Automatic Parking Valet with Unreal Engine Simulation
DESCRIPTION: Use a TD3 agent with an MPC controller to perform a parking maneuver.
PRODUCT:
MATLAB;Simulink;Reinforcement Learning Toolbox;Model Predictive Control Toolbox;Automated Driving Toolbox;Robotics System Toolbox


COMPONENT: rl
EXAMPLENAME: TrainMultipleAgentsForPathFollowingControlExample
EXAMPLETITLE: Train Multiple Agents for Path Following Control
PRODUCT: MATLAB;Reinforcement Learning Toolbox
DESCRIPTION:
Train a DQN and a DDPG agent to collaboratively perform adaptive cruise control and lane keeping assist to follow a path.


COMPONENT: rl
EXAMPLENAME: SimulateASimulinkEnvironmentWithMultipleAgentsExample
EXAMPLETITLE: Simulate Simulink Environment with Multiple Agents
PRODUCT: MATLAB;Reinforcement Learning Toolbox
DESCRIPTION:
Simulate an environment created for the Simulink® model used in the Train Multiple Agents to Perform Collaborative Task example.


COMPONENT: rl
EXAMPLENAME: WaterTankEnvironmentModelExample
EXAMPLETITLE: Water Tank Reinforcement Learning Environment Model
PRODUCT: MATLAB;Reinforcement Learning Toolbox;Simulink
DESCRIPTION:
Create a reinforcement learning Simulink environment that contains an RL Agent block in place of a controller for the water level in a tank.


COMPONENT: rl
EXAMPLENAME: GenerateRewardFunctionFromAModelPredictiveControllerExample
EXAMPLETITLE: Generate Reward Function from a Model Predictive Controller for a Servomotor
PRODUCT: MATLAB;Reinforcement Learning Toolbox;Model Predictive Control Toolbox
DESCRIPTION:
Generate a reward function from an MPC controller applied to a servomotor and use it to train a TD3 agent.


COMPONENT: rl
EXAMPLENAME: CustomTrainingLoopWithSimulinkActionNoiseExample
EXAMPLETITLE: Custom Training Loop with Simulink Action Noise
PRODUCT: MATLAB;Reinforcement Learning Toolbox;Simulink
DESCRIPTION:
Use a custom training loop to train a continuous action space reinforcement learning policy in Simulink when action noise is generated within the model.


COMPONENT: rl
EXAMPLENAME: TrainDDPGAgentWithSupervisedActorForLaneKeepingExample
EXAMPLETITLE: Train DDPG Agent with Pretrained Actor Network
PRODUCT: MATLAB;Reinforcement Learning Toolbox;Simulink
DESCRIPTION:
Train a DDPG agent using an actor network that has been previously trained using supervised learning.


COMPONENT: rl
EXAMPLENAME: TrainAgentsInMultiagentEnvironmentExample
EXAMPLETITLE: Train Agents in Multiagent Environment
PRODUCT: MATLAB;Reinforcement Learning Toolbox
DESCRIPTION:
Train the agents configured in the Train Multiple Agents to Perform Collaborative Task example, within the corresponding environment.


COMPONENT: rl
EXAMPLENAME: TrainMultipleAgentsForAreaCoverageExample
EXAMPLETITLE: Train Multiple Agents for Area Coverage
PRODUCT: MATLAB;Simulink;Reinforcement Learning Toolbox
DESCRIPTION:
Train three discrete action space PPO agents to explore a grid-world environment in a collaborative-competitive manner.


COMPONENT: rl
EXAMPLENAME: GenerateRewardFunctionFromAModelVerificationBlockExample
EXAMPLETITLE: Generate Reward Function from a Model Verification Block for a Water Tank System
PRODUCT: MATLAB;Reinforcement Learning Toolbox;Simulink;Simulink Design Optimization
DESCRIPTION:
Generate a reward function from an model verification block applied to a water tank system and use it to train a TD3 agent.


COMPONENT: rl
EXAMPLENAME: CreateASimulinkEnvironmentUsingAnAgentInTheWorkspaceExample
EXAMPLETITLE: Create Simulink Environment Using Agent in Workspace
PRODUCT: MATLAB;Reinforcement Learning Toolbox
DESCRIPTION:
Create a Simulink environment using the trained agent and corresponding Simulink model from the Create Simulink Environment and Train Agent example.


COMPONENT: rl
EXAMPLENAME: GenerateARewardFunctionFromAVerificationBlockExample
EXAMPLETITLE: Generate Reward Function from Verification Block
PRODUCT: MATLAB;Reinforcement Learning Toolbox;Simulink Design Optimization
DESCRIPTION:
Generate a reinforcement learning reward function from a Simulink Design Optimization model verification block.


COMPONENT: robotics
EXAMPLENAME: GetMassMatrixForManipulatorsInSimulinkExample
EXAMPLETITLE: Get Mass Matrix for Manipulators in Simulink
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Calculate the mass matrix for a robot manipulator using a rigidBodyTree model. In this example, you define a robot model and robot configurations in MATLAB® and pass them to Simulink® to be used with the manipulator algorithm blocks.


COMPONENT: robotics
EXAMPLENAME: GetTransformationsInSimulinkExample
EXAMPLETITLE: Get Transformations for Manipulator Bodies in Simulink
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Get the transformation between bodies in a rigidBodyTree robot model. In this example, you define a robot model and robot configuration in MATLAB® and pass them to Simulink® to be used with the manipulator algorithm block.


COMPONENT: robotics
EXAMPLENAME: BackhoeMotionPlanningUsingRRTExample
EXAMPLETITLE: Motion Planning for Backhoe Using RRT
PRODUCT: MATLAB;Robotics System Toolbox;Simscape Multibody
DESCRIPTION:
Plan a path for a backhoe, in an environment that contains obstacles, by using a motion planner. In this example, you model the backhoe in simplified form as a kinematic tree, then use a sampling-based motion planner to determine a viable path for the backhoe between two poses in the presence of obstacles. Simulate the outcome in a Simscape™ Multibody™ model.


COMPONENT: robotics
EXAMPLENAME: VisualizeManipulatorTrajectoriesWithSimulink3DAnimationExample
EXAMPLETITLE: Visualize Manipulator Trajectory Tracking with Simulink 3D Animation
PRODUCT: MATLAB;Robotics System Toolbox;Simulink;Simulink 3D Animation
DESCRIPTION:
Simulate joint-space trajectories for a rigid body tree robot model and visualize the results with Simulink 3D Animation™.


COMPONENT: robotics
EXAMPLENAME: PerformTrajectoryTrackingAndJointTorqueUsingSimscapeExample
EXAMPLETITLE: Perform Trajectory Tracking and Compute Joint Torque for Manipulator Using Simscape
PRODUCT: Robotics System Toolbox;Simulink;Simscape Multibody;Simscape;MATLAB
DESCRIPTION:
Use Simulink® with Robotics System Toolbox™ to perform trajectory tracking and compute joint torque required to drive the Simscape™ Multibody™ model of the manipulator along the given joint trajectory. This example can be further extended to scenarios with obstacles to observe the changes in torque profile.


COMPONENT: robotics
EXAMPLENAME: TrajectoryControlThroughInverseKinematicsExample
EXAMPLETITLE: Trajectory Control Modeling with Inverse Kinematics
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
This Simulink example demonstrates how the Inverse Kinematics block can drive a manipulator along a specified trajectory.


COMPONENT: robotics
EXAMPLENAME: MultiAgentWithResourceAllocationAndConflictManagementExample
EXAMPLETITLE: Multi-Robot Control with Resource Allocation and Conflict Management
PRODUCT: MATLAB;Robotics System Toolbox;SimEvents
DESCRIPTION:
Control multiple robots working in a distribution center, as well as how to easily configure a distribution system. The robots navigate the facility and complete multiple tasks while leveraging algorithms from game theory to optimize task allocation between robots and resolving conflicts using a grid-based traffic manager. This example builds on the information covered in the Control and Simulate Multiple Robots example, which navigates multiple robots around a similar facility, but this example uses custom algorithms.


COMPONENT: robotics
EXAMPLENAME: RunAndConnectToMultipleGazeboSessionsFromSimulinkExample
EXAMPLETITLE: Run and Connect to Multiple Gazebo Sessions from Simulink
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Run multiple Gazebo sessions in a virtual machine (VM) and connect to these sessions simultaneously from Simulink® using the parsim function.


COMPONENT: robotics
EXAMPLENAME: ModelAndControlAManipulatorArmWithRSTAndSMExample
EXAMPLETITLE: Model and Control a Manipulator Arm with Robotics and Simscape
PRODUCT: MATLAB;Robotics System Toolbox;Simscape
DESCRIPTION:
Execute a pick-and-place workflow using an ABB YuMi robot, which demonstrates how to design robot algorithms in Simulink®, and then simulate the action in a test environment using Simscape™. The example also shows how to model a system with different levels of fidelity to better focus on the associated algorithm design.


COMPONENT: robotics
EXAMPLENAME: APathPlanningAndObstacleAvoidanceInAWarehouseExample
EXAMPLETITLE: A* Path Planning and Obstacle Avoidance in a Warehouse
PRODUCT: MATLAB;Robotics System Toolbox;Navigation Toolbox
DESCRIPTION:
An extension to the Simulate A Mobile Robot in a Warehouse using Gazebo example. The example shows to change the PRM path planner with an A* planner, and add a vector field histogram (VFH) algorithm to avoid obstacles.


COMPONENT: robotics
EXAMPLENAME: ManipulatorTrajectoriesExample
EXAMPLETITLE: Manipulator Shape Tracing in MATLAB and Simulink
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Trace a predefined 3-D shape in space. Following a smooth, distinct path is useful in many robotics applications such as welding, manufacturing, or inspection. A 3-D trajectory is solved in the task space for tracing the MATLAB® membrane and is executed using the Sawyer robot from Rethink Robotics®. The goal is to generate a smooth path for the end effector of the robot to follow based on a set of waypoints.


COMPONENT: robotics
EXAMPLENAME: PerformFruitPickandPlaceUsingUR10InSimulinkAndGazeboExample
EXAMPLETITLE: Detect and Harvest Fruit Using UR10 Manipulator in Gazebo
PRODUCT:
MATLAB;Robotics System Toolbox;Computer Vision Toolbox;Deep Learning Toolbox;Simulink;Navigation Toolbox

DESCRIPTION:
Setup UR10 manipulator and simulate environment in Gazebo simulator to perform fruit pick-and-place application.


COMPONENT: robotics
EXAMPLENAME: IKBlockTrajectoryExample
EXAMPLETITLE: Trace an End-Effector Trajectory with Inverse Kinematics in Simulink
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Use a rigid body robot model to compute inverse kinematics using Simulink®. Define a trajectory for the robot end effector and loop through the points to solve robot configurations that trace this trajectory.


COMPONENT: robotics
EXAMPLENAME: SimulateAMobileRobotInAWarehouseUsingGazeboExample
EXAMPLETITLE: Simulate a Mobile Robot in a Warehouse Using Gazebo
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Simulate a warehouse robot in Gazebo. Gazebo enabled you to simulate a mobile robot that uses a range sensor, while executing certain tasks in a simulated environment. This example details how to use a simulator to apply the Execute Tasks for A Warehouse Robot example, where a robot delivers packages in a warehouse scenario. The robot makes use of the simulated range sensor in Gazebo to detect possible collisions with a dynamic environment and avoid them.


COMPONENT: robotics
EXAMPLENAME: PerformCoSimulationBetweenSimulinkAndGazeboExample
EXAMPLETITLE: Perform Co-Simulation Between Simulink and Gazebo
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Set up a synchronized simulation between Simulink™ and Gazebo to send commands and receive data from Gazebo.


COMPONENT: robotics
EXAMPLENAME: UseCustomTimeScalingForARotationTrajectoryExample
EXAMPLETITLE: Use Custom Time Scaling for a Rotation Trajectory
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Specify custom time-scaling in the Rotation Trajectory block to execute an interpolated trajectory. Two rotations are specified in the block to generate a trajectory between them. The goal is to move between rotations using a nonlinear time scaling with more time samples closer to the final rotation.


COMPONENT: robotics
EXAMPLENAME: PlanPathForABicycleRobotInSimulinkExample
EXAMPLETITLE: Plan Path for a Bicycle Robot in Simulink
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Demonstrates how to execute an obstacle-free path between two locations on a given map in Simulink®. The path is generated using a probabilistic road map (PRM) planning algorithm (mobileRobotPRM). Control commands for navigating this path are generated using the Pure Pursuit controller block. A bicycle kinematic motion model simulates the robot motion based on those commands.


COMPONENT: robotics
EXAMPLENAME: ExecuteTasksForAWarehouseRobotExample
EXAMPLETITLE: Execute Tasks for a Warehouse Robot
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Demonstrates how to execute an obstacle-free path for a mobile robot between three locations on a given map. The robot is expected to visit the three locations in a warehouse: a charging station, loading station, and unloading location. The sequence in which these locations are visited is dictated by a scheduler. The scheduler gives each robot a goal pose to navigate to. The robot plans a path and uses a Pure Pursuit controller to follow the waypoints based on the current pose of the robot. The Differential Drive Kinematic Model block models the simplified kinematics, which takes the linear and angular velocities from the Pure Pursuit Controller. This example builds on top of the Plan Path for a Differential Robot in Simulink example.


COMPONENT: robotics
EXAMPLENAME: ExecuteTransformationTrajectoryUsingManipulatorIKExample
EXAMPLETITLE: Execute Transformation Trajectory Using Manipulator and Inverse Kinematics
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Generate a transformation trajectory using the Transform Trajectory block and execute it for a manipulator robot using inverse kinematics.


COMPONENT: robotics
EXAMPLENAME: ImportSimscapeMultibodyModelToRigidBodyTreeObjectExample
EXAMPLETITLE: Import Simscape™ Multibody™ model to RigidBodyTree Object
PRODUCT: MATLAB;Robotics System Toolbox;Simscape;Simscape Multibody;Simulink
DESCRIPTION:
Import an existing Simscape™ Multibody™ robot model into the Robotics System Toolbox™ as a rigidBodyTree object.


COMPONENT: robotics
EXAMPLENAME: PlanPathForAUnicycleRobotInSimulinkExample
EXAMPLETITLE: Plan Path for a Unicycle Robot in Simulink
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Demonstrates how to execute an obstacle-free path between two locations on a given map in Simulink®. The path is generated using a probabilistic road map (PRM) planning algorithm (mobileRobotPRM). Control commands for navigating this path are generated using the Pure Pursuit controller block. A unicycle kinematic motion model simulates the robot motion based on those commands.


COMPONENT: robotics
EXAMPLENAME: UseCustomTimeScalingForATransformTrajectoryExample
EXAMPLETITLE: Use Custom Time Scaling for Transform Trajectory
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Specify custom time-scaling in the Transform Trajectory block to execute an interpolated trajectory. Two transformations are specified in the block to generate a trajectory between the two. The goal is to move between transforms using a nonlinear time scaling where the trajectory moves quickly at the start and slowly at the end.


COMPONENT: robotics
EXAMPLENAME: ConfigureGazeboAndSimulinkForCosimulationOfManipulatorsExample
EXAMPLETITLE: Configure Gazebo and Simulink for Co-simulation of a Manipulator Robot
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Set up a UR10 robot model to perform co-simulation between Gazebo and Simulink™. Co-simulation with Gazebo enables you to connect directly from Simulink to Gazebo and control simulation pacing using the Simulink model.


COMPONENT: robotics
EXAMPLENAME: ComputeGeometricJacboianForManipulatorsInSimulinkExample
EXAMPLETITLE: Compute Geometric Jacobian for Manipulators in Simulink
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Calculate the geometric Jacobian for a robot manipulator by using a rigidBodyTree model. The Jacobian maps the joint-space velocity to the end-effector velocity relative to the base coordinate frame. In this example, you define a robot model and robot configurations in MATLAB® and pass them to Simulink® to be used with the manipulator algorithm blocks.


COMPONENT: robotics
EXAMPLENAME: DesignPositionControlledManipulatorUsingSimscapeExample
EXAMPLETITLE: Design Position Controlled Manipulator Using Simscape
PRODUCT: Robotics System Toolbox;Simulink;Simscape Multibody;MATLAB;Simscape
DESCRIPTION:
Use Simulink® with Robotics System Toolbox™ to design a position controller for a manipulator and compute joint position required to drive the Simscape™ Multibody™ model of the manipulator.


COMPONENT: robotics
EXAMPLENAME: AvoidObstaclesUsingReinforcementLearningForMobileRobotsExample
EXAMPLETITLE: Avoid Obstacles Using Reinforcement Learning for Mobile Robots
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Uses Deep Deterministic Policy Gradient (DDPG) based reinforcement learning to develop a strategy for a mobile robot to avoid obstacles. For a brief summary of the DDPG algorithm, see Deep Deterministic Policy Gradient Agents.


COMPONENT: robotics
EXAMPLENAME: PlotAckermannDriveVehicleInSimulinkExample
EXAMPLETITLE: Plot Ackermann Drive Vehicle in Simulink
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Plot the position of an Ackermann Kinematic Model block and change the vehicle velocity and steering angular velocity in real-time.


COMPONENT: robotics
EXAMPLENAME: ControlADifferentialDriveRobotInGazeboWithSimulinkExample
EXAMPLETITLE: Control Differential Drive Robot in Gazebo with Simulink
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Control a differential drive robot in Gazebo co-simulation using Simulink®. The robot follows a set of waypoints by reading the pose and wheel encoder positions and generates torque-control commands to drive it.


COMPONENT: robotics
EXAMPLENAME: ComputeVelocityProductForManipulatorsInSimulinkExample
EXAMPLETITLE: Compute Velocity Product for Manipulators in Simulink
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Calculate the velocity-induced torques for a robot manipulator by using a rigidBodyTree model. In this example, you define a robot model and robot configuration in MATLAB® and pass them to Simulink® to be used with the manipulator algorithm blocks.


COMPONENT: robotics
EXAMPLENAME: CalculateManipulatorGravityDynamicsUsingSimulinkExample
EXAMPLETITLE: Calculate Manipulator Gravity Dynamics in Simulink
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Use the manipulator algorithm blocks to compute and compare dynamics due to gravity for a manipulator robot.


COMPONENT: robotics
EXAMPLENAME: PlanPathForADifferentialRobotInSimulinkExample
EXAMPLETITLE: Plan Path for a Differential Drive Robot in Simulink
PRODUCT: MATLAB;Robotics System Toolbox;Simulink
DESCRIPTION:
Demonstrates how to execute an obstacle-free path between two locations on a given map in Simulink®. The path is generated using a probabilistic road map (PRM) planning algorithm (mobileRobotPRM). Control commands for navigating this path are generated using the Pure Pursuit controller block. A differential drive kinematic motion model simulates the robot motion based on those commands.


COMPONENT: robotics
EXAMPLENAME: PerformSafeTrajectoryTrackingRoboticsExample
EXAMPLETITLE: Perform Safe Trajectory Tracking Control Using Robotics Manipulator Blocks
PRODUCT: MATLAB;Robotics System Toolbox;Simscape;Simscape Multibody;Simulink
DESCRIPTION:
Use Simulink® with manipulator algorithm blocks to achieve safe trajectory tracking control of a simulated robot.


COMPONENT: robotics
EXAMPLENAME: PlanAPathForAManipulatorInSimulinkExample
EXAMPLETITLE: Plan Path for Manipulator in Simulink with Robotics System Toolbox
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Execute and simulate a basic path planning task in Simulink®. This example uses code generation to illustrate a pattern for executing autonomy functions from MATLAB® in Simulink.


COMPONENT: robotics
EXAMPLENAME: ControlManipulatorRobotWithCosimulationInGazeboExample
EXAMPLETITLE: Control Manipulator Robot with Co-Simulation in Simulink and Gazebo
PRODUCT: MATLAB;Robotics System Toolbox
DESCRIPTION:
Simulate control of a robotic manipulator using co-simulation between Simulink and Gazebo. The example uses Simulink™ to model the robot behavior, generate control commands, send these commands to Gazebo, and control the pace of the Gazebo simulation.


COMPONENT: robust
EXAMPLENAME: usim_demo
EXAMPLETITLE: Robustness Analysis in Simulink
PRODUCT: MATLAB;Robust Control Toolbox;Simulink
DESCRIPTION:
Specify uncertain systems in Simulink using the Uncertain State Space block. Perform linear analysis and Monte Carlo simulations to analyze the robustness of such systems.


COMPONENT: robust
EXAMPLENAME: LinearizeBlockToUncertainModelExample
EXAMPLETITLE: Linearize Simulink Block to Uncertain Model
PRODUCT: MATLAB;Robust Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Specify an uncertain value as the substitute linearization for a Simulink block at the command line.


COMPONENT: robust
EXAMPLENAME: FindUncertainVariablesInAModelExample
EXAMPLETITLE: Find Uncertain Variables in a Model
PRODUCT: MATLAB;Robust Control Toolbox;Simulink
DESCRIPTION:
Find all Uncertain State Space blocks and uncertain variables in a Simulink® model. First, open the model.


COMPONENT: robust
EXAMPLENAME: UncertainLinearizationOfModelExample
EXAMPLETITLE: Uncertain Linearization of Model
PRODUCT: MATLAB;Robust Control Toolbox;Simulink Control Design;Simulink
DESCRIPTION:
Compute an uncertain linearization of a Simulink® model containing Uncertain State Space blocks. The model rct_ulinearize_uss has three such blocks, each of which references an uncertain uss model in its Uncertain system variable parameter:


COMPONENT: robust
EXAMPLENAME: TuneAndValidateInSimulinkExample
EXAMPLETITLE: Tune and Validate in Simulink
PRODUCT: MATLAB;Robust Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
In Simulink, use hinfstruct to tune the parameters in the genss model you extract from your Simulink model. To validate the result, write the parameters back to the model and simulate the model to evaluate the tuned performance.


COMPONENT: robust
EXAMPLENAME: SimulateUncertainModelAtSampledParameterValuesExample
EXAMPLETITLE: Simulate Uncertain Model at Sampled Parameter Values
PRODUCT: MATLAB;Robust Control Toolbox;Simulink
DESCRIPTION:
Simulate an uncertain model in Simulink® using the Uncertain State Space block. You can sample uncertain parameters at specified values or generate random samples. The MultiPlot Graph block lets you visualize the responses of multiple samples on the same plot.


COMPONENT: robust
EXAMPLENAME: ulinearize_demo
EXAMPLETITLE: Linearization of Simulink Models with Uncertainty
PRODUCT: MATLAB;Robust Control Toolbox;Simulink
DESCRIPTION:
Use Simulink Control Design linearization tools to compute an uncertain state-space ( uss ) model from a system modeled in Simulink .


COMPONENT: robust
EXAMPLENAME: RobustMIMOControllerForTwoLoopAutopilotExample
EXAMPLETITLE: Robust MIMO Controller for Two-Loop Autopilot
PRODUCT: MATLAB;Robust Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Design a controller for a two-loop autopilot that is robust against gain and phase variations in the multichannel feedback loop.


COMPONENT: robust
EXAMPLENAME: ExtractTunableControlSystemFromSimulinkModelExample
EXAMPLETITLE: Extract Tunable Control System from Simulink Model
PRODUCT: MATLAB;Robust Control Toolbox;Simulink;Simulink Control Design
DESCRIPTION:
Create a tunable model for tuning with hinfstruct, starting with a Simulink® model of your control system. To do so:


COMPONENT: robust
EXAMPLENAME: VaryUncertainValuesAcrossMultipleUncertainBlocksExample
EXAMPLETITLE: Vary Uncertain Values Across Multiple Uncertain Blocks
PRODUCT: MATLAB;Robust Control Toolbox;Simulink
DESCRIPTION:
For models with a large number of uncertain variables or multiple Uncertain State Space blocks, you can vary multiple uncertainty values simultaneously.


COMPONENT: ros
EXAMPLENAME: ReadROS2ImageMessagesInSimulinkExample
EXAMPLETITLE: Read ROS 2 Image Messages in Simulink® and Perform Registration using Feature Matching
PRODUCT: MATLAB;ROS Toolbox;Simulink;Computer Vision Toolbox
DESCRIPTION:
Read ROS 2 sensor_msgs/Image messages in Simulink and perform image registration using feature matching.


COMPONENT: ros
EXAMPLENAME: ConnectToAROSenabledRobotFromSimulinkExample
EXAMPLETITLE: Connect to a ROS-enabled Robot from Simulink
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
Configure Simulink to connect to a separate robot simulator using ROS and then send velocity commands, and receive position information from a simulated robot.


COMPONENT: ros
EXAMPLENAME: ConvertAROSPoseMessageToAHomogeneousTransformationExample
EXAMPLETITLE: Convert a ROS Pose Message to a Homogeneous Transformation
PRODUCT: Simulink;ROS Toolbox
DESCRIPTION:
This model subscribes to a Pose message on the ROS network and converts it to a homogeneous transformation.


COMPONENT: ros
EXAMPLENAME: AutomatedParkingValetWithROSInSimulinkExample
EXAMPLETITLE: Automated Parking Valet with ROS in Simulink
PRODUCT: Simulink;Automated Driving Toolbox;ROS Toolbox;Simulink Coder;Embedded Coder
DESCRIPTION:
Distribute an automated parking valet application among various nodes in a ROS network in Simulink .


COMPONENT: ros
EXAMPLENAME: SetStringParameterOnROSNetworkExample
EXAMPLETITLE: Set String Parameter on ROS Network
PRODUCT: MATLAB;ROS Toolbox
DESCRIPTION:
To create your string parameter, use a String Constant block and convert it to uint8 using a MATLAB function block. The converted uint8 string is passed into the Set Parameter block along with the extra input, Length, specified with a second Constant block. The Length refers to the maximum expected string length and is required for all string parameters. For more information, see the Set Parameter block.


COMPONENT: ros
EXAMPLENAME: WorkWithROS2MessagesInSimulinkExample
EXAMPLETITLE: Work with ROS 2 Messages in Simulink
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
Work with complex ROS 2 messages in Simulink , such as messages with nested sub-messages and variable-length arrays.


COMPONENT: ros
EXAMPLENAME: ConnectToAROS2enabledRobotFromSimulinkExample
EXAMPLETITLE: Connect to a ROS-Enabled Robot from Simulink over ROS 2
PRODUCT: Simulink;ROS Toolbox;MATLAB
DESCRIPTION:
Configure a Simulink model to send and receive information from a separate ROS-based simulator such as Gazebo over ROS 2.


COMPONENT: ros
EXAMPLENAME: CompareROSStringParametersExample
EXAMPLETITLE: Compare ROS String Parameters
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
On ROS networks, strings parameters are stored as a uint8 array. When you get from string parameters from the server, they are returned as a char array. In Simulink®, they are cast as uint8, so you must use uint8 character vectors when comparing to the ROS string parameters. You can use this comparison to trigger subsystems for larger models or validate settings for specific algorithms.


COMPONENT: ros
EXAMPLENAME: ReadAROSScanMessageInSimulinkExample
EXAMPLETITLE: Read A ROS Scan Message In Simulink®
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
Read in a laser scan message from a ROS network and calculate the Cartesian coordinate points to visualize with a 2D plot.


COMPONENT: ros
EXAMPLENAME: DeployROS2NodesForAutomatedParkingValetInSimulinkExample
EXAMPLETITLE: Generate and Deploy ROS 2 Nodes for Automated Parking Valet in Simulink
PRODUCT: MATLAB;ROS Toolbox;Simulink;Automated Driving Toolbox;Simulink Coder;Embedded Coder
DESCRIPTION:
After simulating the ROS 2 nodes to verify all the components of the automated parking valet system as described in Simulate Automated Parking Valet with ROS 2 in Simulink, you can now generate code for those ROS 2 nodes and deploy them. Variant subsystem under each node will use publish and subscribe blocks to replace input and output ports.


COMPONENT: ros
EXAMPLENAME: ReadROS2PointCloudMessagesInSimulinkExample
EXAMPLETITLE: Read ROS 2 Point Cloud Messages in Simulink and Perform Stitching Using Registration
PRODUCT: MATLAB;ROS Toolbox;Computer Vision Toolbox;Simulink
DESCRIPTION:
Read ROS 2 PointCloud2 messages into Simulink and reconstruct a 3-D scene by combining multiple point clouds using NDT algorithm.


COMPONENT: ros
EXAMPLENAME: SignFollowingRobotUsingYOLOv2DetectionWithROSExample
EXAMPLETITLE: Sign Following Robot Using YOLOv2 Detection Algorithm with ROS in Simulink
PRODUCT: MATLAB;ROS Toolbox;GPU Coder;Deep Learning Toolbox
DESCRIPTION:
Use Simulink to control a simulated robot running on a separate ROS-based simulator and generate CUDA-optimized code for the ROS node, from the Simulink model, and deploy it to the localhost device.


COMPONENT: ros
EXAMPLENAME: CheckImageEncodingParameterForROSImageMessageExample
EXAMPLETITLE: Check Image Encoding Parameter for ROS Image Message
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
How to access string parameters and use them to trigger subsystem operations. It gets an image format off the set up ROS parameter server. It is retrieved as a uint8 array that is compared using the strcmp MATLAB function block. When a new image is received from the Subscribe block and the format is uint8('jpeg'), it triggers the "Process Image" block to perform a task on the image data.


COMPONENT: ros
EXAMPLENAME: ReadAROSPointCloudMessageInSimulinkRExample
EXAMPLETITLE: Read A ROS Point Cloud Message In Simulink®
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
Read in a point cloud message from a ROS network and calculate the center of mass of the coordinates, and display the point cloud as an image.


COMPONENT: ros
EXAMPLENAME: PlayBackDataFromJackalRosbagLogfileInSimulinkExample
EXAMPLETITLE: Play Back Data from Jackal rosbag Logfile in Simulink
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
Use the Read Data block to play back data from a rosbag log file recorded from a Jackal™ robot from ClearPath™ Robotics.


COMPONENT: ros
EXAMPLENAME: WorkWithROSMessagesInSimulinkExample
EXAMPLETITLE: Work with ROS Messages in Simulink
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
Work with complex ROS messages in Simulink , such as messages with nested sub-messages and variable-length arrays.


COMPONENT: ros
EXAMPLENAME: LaneAndVehicleDetectionInROSUsingYOLOV2algorithmExample
EXAMPLETITLE: Lane and Vehicle Detection in ROS Using YOLO v2 Deep Learning Algorithm
PRODUCT: MATLAB;ROS Toolbox;GPU Coder;Image Processing Toolbox;Computer Vision Toolbox;Deep Learning Toolbox
DESCRIPTION:
Use deep convolutional neural networks inside a ROS enabled Simulink model to perform lane and vehicle detection.


COMPONENT: ros
EXAMPLENAME: CallROS2ServiceInSimulinkExample
EXAMPLETITLE: Call ROS 2 Service in Simulink
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
Call a service on the ROS 2 network in Simulink using the Call Service block and receive a response.


COMPONENT: ros
EXAMPLENAME: GetAndSetROSParametersExample
EXAMPLETITLE: Get and Set ROS Parameters
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
This model gets and sets ROS parameters using Simulink®. This example illustrates how to use ROS parameters in Simulink and to share data over the ROS network. An integer value is set as a parameter on the ROS network. This integer is retrieved from the parameter server and compared to a constant. The output Boolean from the comparison is also set on the network. Change the constant block in the top left (blue) when you run the model to set network parameters based on user input conditions.


COMPONENT: ros
EXAMPLENAME: SimulinkROS2SignTrackingExample
EXAMPLETITLE: Sign-Following Robot with ROS 2 in Simulink
PRODUCT: Simulink;ROS Toolbox
DESCRIPTION:
Use Simulink to control a simulated robot running on a separate ROS-based simulator over ROS 2 network.


COMPONENT: ros
EXAMPLENAME: AutomatedParkingValetWithROS2InSimulinkExample
EXAMPLETITLE: Simulate Automated Parking Valet with ROS 2 in Simulink
PRODUCT: Automated Driving Toolbox;Simulink;ROS Toolbox
DESCRIPTION:
Distribute an automated parking valet application among various nodes in a ROS 2 network in Simulink .


COMPONENT: ros
EXAMPLENAME: DeployROSNodeWithTimeSynchronizationUsingSimulinkExample
EXAMPLETITLE: Deploy ROS Node for Sign Following Robot with Time Synchronization Using Simulink
PRODUCT: MATLAB;ROS Toolbox
DESCRIPTION:
Use Simulink® to generate a ROS stepping enabled node and control a simulated robot running on a separate ROS-based simulator.


COMPONENT: ros
EXAMPLENAME: CreateROS2ServiceServerInSimulinkExample
EXAMPLETITLE: Create ROS 2 Service Server in Simulink
PRODUCT: MATLAB;ROS Toolbox;Simulink
DESCRIPTION:
Set up a ROS 2 service server in Simulink® which provides the vector cross product as response for any two input vectors. You then create a service client, connect to the service server and send a service request with two input vectors.


COMPONENT: rptgen_rptgenext
EXAMPLENAME: RprtOnSimulinkMdlWRprtExplorerExample
EXAMPLETITLE: Report on Simulink Model with Report Explorer
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Use the Report Explorer to report on a Simulink model. You must have Simulink Report Generator installed to run this example.


COMPONENT: rptgenext
EXAMPLENAME: ReportActiveModelConfigurationSetExample
EXAMPLETITLE: Report Active Model Configuration Set
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Use an object of the slreportgen.report.ModelConfiguration class to report on the active model configuration set.


COMPONENT: rptgenext
EXAMPLENAME: IncludeSystemHierarchyOfAModelInAReportExample
EXAMPLETITLE: Include System Hierarchy of a Model in a Report
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Include the system hierarchy of the slrgex_fuelsys model in a report by adding an slreportgen.report.SystemHierarchy reporter to a report generation program. Generate the model diagrams by adding an slreportgen.finder.DiagramFinder object. The system hierarchy reporter generates links from subsystems in the nested list to the corresponding diagrams.


COMPONENT: rptgenext
EXAMPLENAME: IncludeCodeOfUserDefinedSupportingFunctionsInReportExample
EXAMPLETITLE: Include Code of User-Defined Supporting Functions in Report
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
By default, a MATLABFunction reporter includes the code of the main function, but not the code of the user-defined supporting functions that the main function calls. To include the code of the user-defined functions, use the IncludeSupportingFunctionsCode property.


COMPONENT: rptgenext
EXAMPLENAME: TestIfObjectIsABusSelectorExample
EXAMPLETITLE: Test If Object Is a Bus Selector
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
In this case, the Bus Selector1 block in the slrgex_fuelsys_fuel_rate_control model is a Bus Selector block.


COMPONENT: rptgenext
EXAMPLENAME: GetReporterImplementationExample
EXAMPLETITLE: Get Reporter Implementation
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Use getImpl to obtain the DOM object used to create a diagram reporter. You can use the getImpl method with any type of reporter.


COMPONENT: rptgenext
EXAMPLENAME: ObtainStateflowChartSlSfHandleExample
EXAMPLETITLE: Obtain Stateflow Chart Handle
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Returns the list of Stateflow chart properties to the workspace. The Stateflow handle is equivalent to the Stateflow object. To use a Stateflow handle, assign it to a variable.


COMPONENT: rptgenext
EXAMPLENAME: CustomizeTheFormattingOfModelVariablesInAReportExample
EXAMPLETITLE: Customize the Formatting of Model Variables in a Report
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Customize the formatting of model variables in a report by iterating through the search results and setting properties of the model variable reporter for each result.


COMPONENT: rptgenext
EXAMPLENAME: ReportOnLookupTableBlockExample
EXAMPLETITLE: Report on Lookup Table Block
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Create a PDF report generator that reports on a lookup table block. This example uses the sf_car model and reports on its engine torque Lookup Table (n-D) block. This block is a 2-D lookup table. The engine torque block is in the Engine subsystem of the sf_car model. The report, by default, includes a table of output values versus breakpoints, a surface plot, a table of block data types, and notes about possible differences between reported values and values obtained from simulation.


COMPONENT: rptgenext
EXAMPLENAME: ReportAMATLABFunctionBlockExample
EXAMPLETITLE: Report a MATLAB Function block
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
To include information about a MATLAB Function block in a report, use an slreportgen.report.MATLABFunction reporter. By default, the report includes a table of object properties, a table of input and output arguments, and the function script.


COMPONENT: rptgenext
EXAMPLENAME: AddSummaryTableReporterToReportExample
EXAMPLETITLE: Add Summary Table Reporter to Report
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Add a summary table for finder results respresenting named signals in your Simulink® model to a report.


COMPONENT: rptgenext
EXAMPLENAME: CreateAListOfVariablesWithLinksToContentExample
EXAMPLETITLE: Create a List of Variables with Links to Content
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
You can use the variable ID returned by the getVariableID method to create a link to the reported content for the variable. This example generates a report of the variables used by the sf_car model. The list of variables at the beginning of the report provides links to the reported content for the variables.


COMPONENT: rptgenext
EXAMPLENAME: CustomizeReporterForSignalResultExample
EXAMPLETITLE: Customize Reporter for Signal Result
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Use the getReporter method of an slreportgen.finder.SignalResult object to access the signal reporter for the result. Then, customize the reporter by setting its properties.


COMPONENT: rptgenext
EXAMPLENAME: FindAndReportSignalsInAModelExample
EXAMPLETITLE: Find and Report Signals in a Model
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Creates a report that includes information about signals in a model by using an slreportgen.finder.SignalFinder object. The example sets the finder properties so that signals without names are excluded and internal signals are included.


COMPONENT: rptgenext
EXAMPLENAME: FindStateflowDataAndEventsExample
EXAMPLETITLE: Find Stateflow Data and Events
PRODUCT: MATLAB;Simulink Report Generator;Simulink;MATLAB Report Generator
DESCRIPTION:
Create a report that finds Stateflow data and events in the shift_logic Stateflow chart within the sf_car model.


COMPONENT: rptgenext
EXAMPLENAME: FindAndReportOnStateflowElementsExample
EXAMPLETITLE: Find and Report on Stateflow Elements
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Describes how to find and report on Stateflow states, transitions, and junctions. It reports on the control_logic chart of the slrgex_fuelsys_fuel_rate_control model.


COMPONENT: rptgenext
EXAMPLENAME: FindStateflowStatesExample
EXAMPLETITLE: Find Stateflow States
PRODUCT: MATLAB;Simulink Report Generator;Simulink;MATLAB Report Generator
DESCRIPTION:
Create a report that includes properties of all the Stateflow states in the shift_logic chart of the sf_car model.


COMPONENT: rptgenext
EXAMPLENAME: ExecutionOrderOfTasksAndBlocksExample
EXAMPLETITLE: Report Execution Order of Tasks and Blocks in Simulink Systems
PRODUCT: MATLAB;Simulink Report Generator;Simulink
DESCRIPTION:
Use an slreportgen.report.ExecutionOrder reporter to report on the tasks executed by a model and the order in which the blocks execute during each task.


COMPONENT: rptgenext
EXAMPLENAME: IncludeModelNotesInAReportExample
EXAMPLETITLE: Include Model Notes in a Report
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Reports the notes for the sldemo_autotrans model. This example reports the notes for the overall model. For an example that reports the diagram and notes for each subsystem of the model, see Report Model Notes.


COMPONENT: rptgenext
EXAMPLENAME: FindAndReportOnBlocksInAModelExample
EXAMPLETITLE: Find and Report on Blocks in a Model
PRODUCT: MATLAB;Simulink Report Generator;Simulink;MATLAB Report Generator
DESCRIPTION:
Find and report on all Simulink blocks in the slrgex_vdp model using the BlockFinder class. The resulting HTML report includes default information and uses default formatting for each block.


COMPONENT: rptgenext
EXAMPLENAME: CheckIfBlockIsAStateTransitionTableBlockExample
EXAMPLETITLE: Check If Block Is a State Transition Table Block
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
In this case, the downshifting object in the Stateflow shift_logic chart of the sf_car model is not a State Transition Table block.


COMPONENT: rptgenext
EXAMPLENAME: ReportSystemTasksAndTaskBlocksInExecutionOrderExample
EXAMPLETITLE: Report System Tasks and Task Blocks in Execution Order
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
For each block diagram or virtual subsystem of the slrgex_vdp model, report the system tasks and the blocks in each task, in execution order.


COMPONENT: rptgenext
EXAMPLENAME: IncludeMATLABFunctionArgumentDetailsInReportExample
EXAMPLETITLE: Include MATLAB Function Argument Details in Report
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
To include the MATLAB function argument details in a report, use the IncludeArgumentProperties property of the MATLABFunction reporter.


COMPONENT: rptgenext
EXAMPLENAME: AddModelVariablesToAReportExample
EXAMPLETITLE: Add Model Variables to a Report
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Find the variables in a model and add the results directly to a report. Specify that the finder includes variables in masked systems.


COMPONENT: rptgenext
EXAMPLENAME: GenerateNumberThatRepresentsSubsystemInModelHierarchyExample
EXAMPLETITLE: Generate Number That Represents Subsystem Position in Model Hierarchy
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Create an slreportgen.utils.HierarchyNumber object for the slrgex_f14 model and generate the number that represents the position of the Aircraft Dynamics Model subsystem in the model hierarchy.


COMPONENT: rptgenext
EXAMPLENAME: AddStateflowFunctionDiagramToReportExample
EXAMPLETITLE: Add Stateflow Function Diagram to Report
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
The sf_car model uses a Simulink Function, which is a function that uses a Simulink subsystem to compute its outputs from its inputs. This example finds the diagrams in the model and for each diagram uses an slreportgen.DiagramElementFinder object to find the Simulink Function subsystems. For each slreportgen.DiagramElementResult object returned by the finder, the example uses the Name property value as a section title and calls the getDiagramReporter method to return the subsystem diagram to add to the section.


COMPONENT: rptgenext
EXAMPLENAME: FindAllBlockDiagramsAndStateflowChartsExample
EXAMPLETITLE: Find All Block Diagrams and Stateflow Charts
PRODUCT: MATLAB;Simulink Report Generator;Simulink;MATLAB Report Generator
DESCRIPTION:
Create a report that includes an image of all diagrams in the sf_car model. Although the model used in this example does not contain model references, the example uses iterator mode to illustrate its syntax.


COMPONENT: rptgenext
EXAMPLENAME: ExportMultipleModelsToAWebViewExample
EXAMPLETITLE: Export Multiple Models to a Web View
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
The export options in this example allow you to view the subsystem that implements the Simulink library block, Band-Limited White Noise, in the f14 model and the Stateflow® chart that implements the Engine block in the sf_car model. If the example did not enable the export options, the subsystem and chart would appear only as blocks in the exported web view.


COMPONENT: rptgenext
EXAMPLENAME: AddHyperlinkedDiagramToAReportExample
EXAMPLETITLE: Add Hyperlinked Diagram to a Report
PRODUCT: MATLAB;Simulink Report Generator;Simulink;MATLAB Report Generator
DESCRIPTION:
Create a PDF report and add diagram snapshots of the root system and a subsystem from the sf_car model to it. Add a hyperlink to the transmission subsystem and add a paragraph as the target for that link.


COMPONENT: rptgenext
EXAMPLENAME: AddPropertiesTableToReportExample
EXAMPLETITLE: Add Properties Table to Report
PRODUCT: MATLAB;Simulink Report Generator;Simulink;MATLAB Report Generator
DESCRIPTION:
Use the SimulinkObjectProperties reporter to add a properties table for the slrgex_vdp model to the report.


COMPONENT: rptgenext
EXAMPLENAME: FindAllDiagramsInASubsystemExample
EXAMPLETITLE: Find All Diagrams in a Subsystem
PRODUCT: MATLAB;Simulink Report Generator;Simulink;MATLAB Report Generator
DESCRIPTION:
Open the sf_car model and find all the diagrams in its Engine subsystem. Use either the path to the subsystem or its handle. You can then include the results in your report.


COMPONENT: rptgenext
EXAMPLENAME: ChangeTheMATLABFunctionScriptFormattingAndTitleExample
EXAMPLETITLE: Change the MATLAB Function Script Formatting and Title
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
To customize the title of the function script section, use the FunctionScriptTitle property. To change the formatting of the code, create a DOM paragraph that specifies the font family, size, and color and assign the paragraph to the FunctionScript property.


COMPONENT: rptgenext
EXAMPLENAME: SortTopToBottomExample
EXAMPLETITLE: Sort Simulink® Blocks from Top to Bottom
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Use the slreportgen.utils.sortBlocks function to sort model blocks by their location in the model layout from top to bottom.


COMPONENT: rptgenext
EXAMPLENAME: TestIfObjectIsATestSequenceExample
EXAMPLETITLE: Test If Object Is a Test Sequence
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
In this case, the Debouncer_Test block in the slrgex_sltestTestSequenceDebouncerExample model is a Test Sequence block.


COMPONENT: rptgenext
EXAMPLENAME: FindStateflowStatesAndTransitionsExample
EXAMPLETITLE: Find Stateflow States and Transitions
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Create a report that finds Stateflow states and transitions in the slrgex_fuelsys_fuel_rate_control model.


COMPONENT: rptgenext
EXAMPLENAME: UseHierarchyNumbersInSectionTitlesExample
EXAMPLETITLE: Use Hierarchy Numbers in Section Titles
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Generates the hierarchy number for each diagram in a model and uses the number in the title of the report section that corresponds to the diagram.


COMPONENT: rptgenext
EXAMPLENAME: CopyASimulinkReporterObjectExample
EXAMPLETITLE: Copy a Simulink Reporter Object
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Copies a DocBlock reporter to show the effect of a deep copy operation on a reporter property. Modifying a property of the Text object in the TextFormatter property of the copy of the DocBlock object does not affect the original DocBlock object.


COMPONENT: rptgenext
EXAMPLENAME: ChangeLookupTablePlotHeightAndWidthExample
EXAMPLETITLE: Change Lookup Table Plot Height and Width
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Create a PDF report generator that specifies the plot height and width returned by the LookupTable reporter. This example uses the sf_car model and reports on its Torque ratio Lookup Table (n-D) block. This block is a 1-D lookup table and is in the transmission/Torque Converter subsystem of the sf_car model. To set the height and width of the plot, use the PlotReporter property.


COMPONENT: rptgenext
EXAMPLENAME: ReportOnInputsAndOutputsOfAModelExample
EXAMPLETITLE: Report on Inputs and Outputs of a Model
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Uses an slreportgen.report.SystemIO reporter to report on the inputs and outputs of a model and its subsystems.


COMPONENT: rptgenext
EXAMPLENAME: FindStateflowChartsExample
EXAMPLETITLE: Find Stateflow Charts
PRODUCT: MATLAB;Simulink Report Generator;Simulink;MATLAB Report Generator
DESCRIPTION:
Create a report that includes images of all Stateflow charts in the sldemo_fuelsys model. Use a separate chapter for each chart.


COMPONENT: rptgenext
EXAMPLENAME: GetActiveConfigurationSetToBeReportedExample
EXAMPLETITLE: Get Active Configuration Set to be Reported
PRODUCT: MATLAB;Simulink Report Generator;MATLAB Report Generator;Simulink
DESCRIPTION:
Create an slreportgen.report.ModelConfiguration reporter for the sf_car model and then get the active configuration set object associated with the reporter.


COMPONENT: rptgenext
EXAMPLENAME: SortLeftToRightExample
EXAMPLETITLE: Sort Simulink® Blocks from Left to Right
PRODUCT: MATLAB;Simulink Report Generator
DESCRIPTION:
Use the slreportgen.utils.sortBlocks function to sort model blocks by their location in the model layout from left to right.


COMPONENT: satcom_whdl
EXAMPLENAME: GPSHDLDataDecodeExample
EXAMPLETITLE: GPS HDL Data Decode and Position Estimation
PRODUCT: MATLAB;Simulink;Wireless HDL Toolbox;Satellite Communications Toolbox;Navigation Toolbox
DESCRIPTION:
Perform bit synchronization and frame synchronization, data decoding, and position estimation on GPS LNAV symbols.


COMPONENT: satcom_whdl
EXAMPLENAME: GPSHDLAcquisitionAndTrackingUsingCACodeExample
EXAMPLETITLE: GPS HDL Acquisition and Tracking Using C/A Code
PRODUCT: MATLAB;Simulink;Wireless HDL Toolbox;Satellite Communications Toolbox
DESCRIPTION:
Acquire and track multiple GPS satellite signals using HDL code generation optimized Simulink® blocks and hardware.


COMPONENT: satcom_whdl
EXAMPLENAME: CCSDSTMHDLReceiverExample
EXAMPLETITLE: CCSDS TM HDL Receiver
PRODUCT: MATLAB;Wireless HDL Toolbox;Satellite Communications Toolbox
DESCRIPTION:
Implement Consultative Committee for Space Data Systems (CCSDS) Telemetry (TM) receiver using Simulink® blocks.


COMPONENT: sdl
EXAMPLENAME: VehicleWithFourSpeedTransmissionExample
EXAMPLETITLE: Vehicle with Four-Speed Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A complete vehicle with Simscape™ Driveline™ components, including the engine, drivetrain, four-speed transmission, tires, and longitudinal vehicle dynamics. The transmission controller is implemented as a state machine in Stateflow®, selecting the gear based on throttle and vehicle speed.


COMPONENT: sdl
EXAMPLENAME: VehicleInSimscapeDrivelineAndSimulinkExample
EXAMPLETITLE: Vehicle in Simscape Driveline and Simulink
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Two equivalent simplified vehicles modeled in Simscape™ Driveline™ and Simulink®. The simulation results are identical, and the Simscape Driveline model is easily extensible to include different effects and a higher level of modeling fidelity. Meshing losses in the gears and more detailed tire modeling can be added without introducing algebraic loops.


COMPONENT: sdl
EXAMPLENAME: VehicleWithManualTransmissionExample
EXAMPLETITLE: Vehicle with Manual Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A vehicle that has a four-speed manual transmission. The key elements of the transmission are four synchronizers. By engaging or disengaging these synchronizers and associated dog clutches, the transmission provides four ratios 3.581, 2.022, 1.384, and 1, respectively. The synchronizers are modeled using the Cone Clutch and Dog Clutch blocks.


COMPONENT: sdl
EXAMPLENAME: VehicleWithFourWheelDriveExample
EXAMPLETITLE: Vehicle with Four-Wheel Drive
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A four-wheel drive vehicle starting from rest and ascending a 15 degree incline. Initially the vehicle rolls backwards until the engine develops sufficient torque to counter the slope. The tire compliance dynamics can be seen as the vehicle starts to accelerate. The model variant chosen for all of the tires can be set to the Simple, Friction Parameterized, or Magic Formula tire model using the hyperlinks in the model.


COMPONENT: sdl
EXAMPLENAME: TireParameterAndPerformanceExample
EXAMPLETITLE: Tire Parameterization and Performance
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Use Simscape™ Driveline™ to fit tire Magic Formula coefficients to experimental data and to measure the simulated stopping distance of a vehicle supported by the tires. The example uses the sdlUtility.tirread function to load initial tire parameters from a .TIR file. Then, the example uses the MATLAB® optimization function fminsearch with a test harness model to fit the tire coefficients to the experimental data. Other products available for performing this type of parameter fitting with Simscape Driveline models are the Optimization Toolbox™ and Simulink® Design Optimization™. These products provide predefined functions to manipulate and analyze blocks using GUIs or a command line approach. This example uses Fast Restart to quickly simulate tire response for different parameters during the optimization.


COMPONENT: sdl
EXAMPLENAME: VehicleFourWheelDriveTestbedExample
EXAMPLETITLE: Four-Wheel Drive Testbed
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A four-wheel drive vehicle with open and limited slip differentials. The front and rear differentials can be standard or Type I Torsen. The center differential can be a solid shaft, viscous coupling, viscous coupling with a locking clutch, or open with no torque transfer. The differential options are in variant subsystems. The variants can be selected using the hyperlinks embedded in the model.


COMPONENT: sdl
EXAMPLENAME: VehicleWithDualClutchTransmissionExample
EXAMPLETITLE: Vehicle with Dual Clutch Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A vehicle with a five-speed dual-clutch transmission. Gear shifts are implemented via the two clutches, one clutch pressure being ramped up as the other clutch pressure is ramped down. Gear pre-selection via dog clutches ensures that the correct gear is fully selected before the on-going clutch is enabled.


COMPONENT: sdl
EXAMPLENAME: TwoModeHybridTransmissionExample
EXAMPLETITLE: Two Mode Hybrid Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
The basic architecture of a two mode hybrid transmission. It consists of three planetary gear sets and four clutches. This combination permits four fixed gear ratios plus two power-split modes. The power split modes are used to transition between fixed gear ratios and for heavy acceleration/deceleration. The fixed ratios help with efficiency when cruising. For the first power split (input-split regime), only Clutch 1 is engaged. For the second power split (compound-split regime), only Clutch 2 is engaged. Engaging two clutches simultaneously removes one degree of freedom and hence results in a fixed ratio.


COMPONENT: sdl
EXAMPLENAME: TorsenDifferentialExample
EXAMPLETITLE: Torsen Differential
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A comparison between the behavior of an open differential and a Torsen limited slip differential. The Torsen differential is modeled using components from the Gears library in Simscape™ Driveline™. Slip is limited in the Torsen differential because it uses non-backdrivable worm gears, which are modeled by Sun-Planet Worm Gear components. The result is higher torque applied to the wheel with greater traction, and identical speeds for the left and right axles.


COMPONENT: sdl
EXAMPLENAME: LimitedSlipDifferentialWithClutchesExample
EXAMPLETITLE: Limited Slip Differential with Clutches
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A comparison between the behavior of an open differential and a limited slip differential with clutch packs. The limited slip differential is modeled using components from the Gears library and Clutches library in Simscape™ Driveline™. Wheel slip is limited by clutches that engage when the torque applied to the input of the differential exceeds a threshold. The clutches lock the differential so that the output shafts of the differential spin at the same speed.


COMPONENT: sdl
EXAMPLENAME: EngineBrakingExample
EXAMPLETITLE: Engine Braking
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A diesel engine equipped with a Jake Brake (R) or compression release engine brake. This type of brake is activated by the driver to slow the vehicle without relying on friction braking mechanisms. Air is released from a number of cylinders at the end of their compression strokes. In this example, the driver can dynamically select to activate braking on zero to eight cylinders. The braking torque for each cylinder is set using a lookup table with engine speed as the input.


COMPONENT: sdl
EXAMPLENAME: PistonEngineTestbedExample
EXAMPLETITLE: Piston Engine Testbed
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
The effect of varying the number of cylinders in a piston engine. Four, six, and eight cylinder engines are included with firing offsets evenly distributed about their four-stroke cycles. Piston pressures are normalized by the number of cylinders to emphasize the effect on output vibration.


COMPONENT: sdl
EXAMPLENAME: CrankAngleResolvedEngineExample
EXAMPLETITLE: Crank-Angle-Resolved Engine Model
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A 2.0-liter, four-cylinder, naturally aspirated, spark-ignited, four-stroke engine which computes crank-angle-resolved instantaneous torque.


COMPONENT: sdl
EXAMPLENAME: SingleCylinderSparkIgnitionEngineExample
EXAMPLETITLE: Single Cylinder Spark Ignition Engine
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A crank-angle-resolved, naturally aspirated, spark ignited single cylinder engine. This example varies control inputs including the spark angle and the intake VVT during the simulation.


COMPONENT: sdl
EXAMPLENAME: ShipPropellerExample
EXAMPLETITLE: Ship Propeller
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A marine propeller represented by a Propeller block from the Simscape™ Driveline™ library that propels a ship. The propeller starts from rest while the current pushes the ship forward. The ship accelerates as the Ideal Angular Velocity Source starts up the propeller. After 500 seconds, the propeller spins at a constant speed, and the ship approaches a constant speed. Ship motion is resisted by a drag force that increases quadratically with ship speed.


COMPONENT: sdl
EXAMPLENAME: FiveSpeedTransmissionExample
EXAMPLETITLE: Five-Speed Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A five-speed transmission with a reverse gear. An engine spins the layshaft and the six sets of output gears. To engage the selected gear, ideal actuators move the selector levers connected to the double-sided synchronizers. The position of the selector levers determines which gears are connected to the output shaft.


COMPONENT: sdl
EXAMPLENAME: CRCRFourSpeedTransmissionExample
EXAMPLETITLE: CR-CR Four-Speed Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A four-speed transmission with two planetary gears and five clutches. The test sequence steps through the four forward gear ratios, switches to neutral, and then applies a brake clutch to the output shaft of the transmission.


COMPONENT: sdl
EXAMPLENAME: RavigneauxFourSpeedTransmissionExample
EXAMPLETITLE: Ravigneaux Four-Speed Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A test harness for a Ravigneaux 4-speed transmission. The subsystem uses the Ravigneaux Gear block and five friction clutches to implement four forward ratios plus reverse. Meshing losses are enabled in the Ravigneaux gear. The clutch states required to implement the different ratios can be viewed by opening the Clutch Schedule block.


COMPONENT: sdl
EXAMPLENAME: SimpsonThreeSpeedTransmissionExample
EXAMPLETITLE: Simpson Three-Speed Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A Simpson transmission with three forward speeds and one reverse speed. Two planetary gear sets are linked with a common sun gear. Two disk friction clutches and two band brakes determine which components can rotate relative to one another which determines the final gear ratio. The Clutch Schedule subsystem shows which clutches and brakes should be locked for each forward or reverse speed.


COMPONENT: sdl
EXAMPLENAME: TwoSpeedTransmissionExample
EXAMPLETITLE: Two-Speed Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A simple two-speed transmission. Two clutches control which gear is selected. A brake is connected to the output shaft and can be controlled independently.


COMPONENT: sdl
EXAMPLENAME: HelicopterTransmissionExample
EXAMPLETITLE: Helicopter Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A fixed helicopter transmission testbed. The gasoline engine provides power that is sent to the main and tail rotors through planetary gearsets. The main rotor shaft is considered rigid, and flexibility is modeled in the longer, thinner tail rotor shaft. Blade pitch angle is set directly via a physical signal. Swash plate dynamics can be added using the appropriate blocks in Simscape™ Fluids™. The engine stalls after six seconds, but lift is maintained for some time through the unidirectional clutch. This scheme also allows autorotation of the main rotor in a descending helicopter.


COMPONENT: sdl
EXAMPLENAME: TransmissionTestbedExample
EXAMPLETITLE: Transmission Testbed
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A testbed with interchangeable transmissions. The transmission models vary from classic four speed transmissions to modern seven, eight, nine, and ten speed configurations. The efficiency and drive ratio can be adjusted by varying the components in each individual transmission configuration. The transmission choices are held in a variant subsystem and are selected by either using the hyperlinks in the model or right-clicking the Transmission subsystem, selecting Variant -> Override using, and the desired variant.


COMPONENT: sdl
EXAMPLENAME: TransmissionFaultDetectionExample
EXAMPLETITLE: Transmission Fault Detection Harness
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Inject stuck-off and stuck-on clutch faults into a transmission system, iterate through failure scenarios to gather synthetic training data sets, apply the data to a basic fault classifier algorithm, and measure the classifier's accuracy. This example uses Fast Restart mode to iterate through many different scenarios without needing to recompile the model in between iterations. This workflow is useful for tuning and testing different transmission fault sensor configurations and detector algorithms.


COMPONENT: sdl
EXAMPLENAME: PowerSplitHybridTransmissionExample
EXAMPLETITLE: Power-Split Hybrid Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
The basic architecture of a power-split hybrid transmission. The planetary gear, along with the motor and generator, acts like a variable ratio gear. In this test, the vehicle accelerates, maintains the faster speed, and then decelerates back to the original speed. The power management strategy uses just stored electrical power to effect the maneuver, the combustion engine only delivering the power required to maintain the original speed.


COMPONENT: sdl
EXAMPLENAME: ParallelHybridTransmissionExample
EXAMPLETITLE: Parallel Hybrid Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
The basic architecture of a parallel hybrid transmission. Electrical power is applied in parallel with the combustion engine power. The electrical torque is applied at the wheel axle, but it could also be applied to the engine flywheel. In this test, the vehicle accelerates, maintains the faster speed, and then decelerates back to the original speed. The power management strategy uses just electrical power to effect the maneuver, the combustion engine only delivering the power required to maintain the original speed.


COMPONENT: sdl
EXAMPLENAME: SeriesHybridTransmissionExample
EXAMPLETITLE: Series Hybrid Transmission
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
The basic architecture of a series hybrid transmission. All mechanical power from the engine is converted to electrical power via the generator. In this test, the vehicle accelerates, maintains the faster speed, and then decelerates back to the original speed. The power management strategy uses just stored electrical power to effect the maneuver, the combustion engine only delivering the power required to maintain the original speed.


COMPONENT: sdl
EXAMPLENAME: ClutchesForAcceleratingAndBrakingExample
EXAMPLETITLE: Clutches for Accelerating and Braking
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
The use of clutches to accelerate and decelerate a pair of shafts connected by a gearbox. The gear connects the output and intermediate shafts. The inertia for both of these shafts is included in the Inertia Output Shaft component. This pair of shafts is connected via one clutch to a drive shaft which is driven by a torque. These shafts are also connected via a second clutch to a stationary point.


COMPONENT: sdl
EXAMPLENAME: HydraulicallyActuatedDrivelineClutchExample
EXAMPLETITLE: Hydraulically-Actuated Driveline Clutch
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
An engine driving an inertial load via a hydraulically-controlled clutch. It shows how Simscape™ Driveline™ can be used in conjunction with Foundation Library isothermal liquid blocks to model hydraulically-actuated drivelines.


COMPONENT: sdl
EXAMPLENAME: CustomClutchExample
EXAMPLETITLE: Custom Clutch
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Two inertias coupled by a simple gear controlled by a clutch. Initially, the clutch pressure is zero, and the inertias have zero velocity. A constant torque is applied to Inertia 1. Once the clutch pressure starts increasing from zero at 2 seconds, Inertia 2 starts spinning, then locks with Inertia 1. From 6 to 7 seconds, the clutch pressure is ramped down to zero, and Inertia 2 starts to spin freely once the clutch unlocks. Because there is no frictional loss, it keeps spinning.


COMPONENT: sdl
EXAMPLENAME: SimpleGearExample
EXAMPLETITLE: Simple Gear
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A simple gear coupling two inertias (shafts). The gear ratio between the follower (F) and base (B) is 2:1. Thus the angular velocity of the follower shaft is half the angular velocity of the base shaft. The follower shaft torque is twice the base shaft torque.


COMPONENT: sdl
EXAMPLENAME: VariableRatioGearExample
EXAMPLETITLE: Variable Ratio Gear
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A variable ratio gear coupling two inertias (shafts). The gear ratio between the follower (F) and the base (B) is steadily increased from 1:1 to 2:1. The ratio of the follower to base angular speed decreases with gear ratio, and conversely the ratio of the follower to base torque increases with gear ratio. The variable gear is implemented using the Variable Ratio Transmission block which includes compliance. Appropriate stiffness and damping values for the compliance will depend upon the levels of torque transmitted by the variable gear. If the compliance damping is unrealistically low, the system can develop high frequency oscillations that require small simulation time steps.


COMPONENT: sdl
EXAMPLENAME: GearWithBacklashExample
EXAMPLETITLE: Gear with Backlash
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Model a gear with backlash using the Simple Gear block with two different backlash models: a spring-damper model and a coefficient of restitution model. The backlash is set to 1 mm, which is equivalent to 0.032 degrees rotation of the input gear that has a radius of 100 mm or 0.016 degrees rotation of the output gear that has a radius of 200 mm. Parameters in the two backlash models are adjusted so that there are a few oscillations when the torque is applied, and the models have similar behavior.


COMPONENT: sdl
EXAMPLENAME: GearboxEfficiencyMeasurementExample
EXAMPLETITLE: Gearbox Efficiency Measurement
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A test for measuring gear box efficiency. The input shaft is driven at a fixed speed and a variable torque is applied to the output shaft. Power is measured on both the input and output shafts, and efficiency is calculated as the ratio of output to input power. The simulation results match the parameters specified for the efficiency of the gear.


COMPONENT: sdl
EXAMPLENAME: EpicyclicGearEfficiencyMeasurementExample
EXAMPLETITLE: Epicyclic Gear Efficiency Measurement
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
An epicyclic gear drive with overall ratio of 256:1 and verifies its transmission efficiency given the individual gear meshing efficiencies. The example is based on Tuplin, W.A. "Designing Compound Epicyclic Gear Trains for Maximum Speed at High Velocity Ratios", Machine Design, April 4, 1957. The drive is built of two ring-planet elements as shown in the gearbox schematic. The example confirms the transmission efficiency value of 0.22 as predicted by the analytical analysis presented in the paper.


COMPONENT: sdl
EXAMPLENAME: CustomPlanetaryGearExample
EXAMPLETITLE: Custom Planetary Gear
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Illustrates how you can build your own custom planetary gear components from the Simscape™ Driveline™ Planetary Subcomponents library. The example is based on Example 10.7 published in K.J. Waldron, G.L. Kinzel "Kinematics, Dynamics, and Design of Machinery", 1999. It consists of a coupled planetary train built from simple and compound planetary trains with a common carrier and bevel gears. The simple train fundamental train ratio is -N_4/N_2 * N_7/N_4 = -N_7/N_2. It connects shafts S2 and S7. The compound planetary train fundamental ratio is -N_4/N_2 * N_6/N_5 and it connects shafts S2 and S6. When the input shaft of the train is rotated at 100 rpm, the model shows the output shaft rotates at 1.4456 rpm as given in the reference.


COMPONENT: sdl
EXAMPLENAME: ShaftWithTorsionalFlexibilityExample
EXAMPLETITLE: Flexible Shaft
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Two flexible aluminum shafts modeled using a lumped parameter approach. Both shafts consist of 20 segments containing inertias, damping, and stiff torsional springs. At the start of the simulation, the clutch is unlocked and the driven shaft is free. Note that the initial velocity of the motor shaft is set to 200 rad/s and that the system starts at steady state. The clutch engages and disengages during the test, and during each event the effect of the shaft flexibility can be seen in the simulation results.


COMPONENT: sdl
EXAMPLENAME: ShaftWithTorsionalAndTransverseFlexibilityExample
EXAMPLETITLE: Shaft with Torsional and Transverse Flexibility
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Two flexible shafts that have torsional and transverse flexibility. One shaft computes transverse motion using computed eigenmodes, and the other shaft uses a lumped parameter approach. The boundary conditions on the shafts can be changed on the block masks.


COMPONENT: sdl
EXAMPLENAME: RatchetLeadscrewMechanismExample
EXAMPLETITLE: Ratchet Leadscrew Mechanism
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A stepping mechanism constructed from a self-locking leadscrew and a unidirectional clutch. The input shaft of the unidirectional clutch oscillates with velocity amplitude 2 rad/s and frequency 0.5 rad/s. The unidirectional clutch drives the load via the leadscrew. The lead angle of the screw is small enough to ensure self-locking operation due to geometry and thread friction. As a result, the load maintains its position while the clutch input shaft rotates in the opposite direction and the load moves in incremental steps of about 25 mm.


COMPONENT: sdl
EXAMPLENAME: SteppingMechanismWithDetentsExample
EXAMPLETITLE: Stepping Mechanism with Detents
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A mass moving along a slider and held at set points with translational detents. The mass is suspended between two springs and is subject to viscous friction. Three detents hold the load at 50, 75, and 125 mm. The peak force of these detents is 20, 30, and 20 N respectively. To move the load past each detent, the spring pushing the load must deform enough to produce a force that overcomes the holding force of the detents.


COMPONENT: sdl
EXAMPLENAME: PowerWindowSystemExample
EXAMPLETITLE: Power Window System
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A motor-driven power window system. A DC motor drives the power window mechanism via a self-locking worm gear with the ratio 1 : 50. The power window mechanism consists of a cable drum and four pulleys all connected by a cable. The window is attached to the cable at two points by the lift plate. This ensures both sides of the window move at the same speed and in the same direction, keeping the window level. The model also includes viscous friction in the guide rails.


COMPONENT: sdl
EXAMPLENAME: SheetMetalFeederExample
EXAMPLETITLE: Sheet Metal Feeder
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A feeding mechanism of a sheet metal cutter. Two slitted rolls are driven by a torque motor through two mechanical drivetrains. Each drivetrain consists of a spur gear train, worm gear, and a chain drive. The sprocket of the chain drive is connected to its respective slitted roll. The interaction between the rolls and the sheet metal is simulated by the Loaded Contact Translational Friction blocks.


COMPONENT: sdl
EXAMPLENAME: HydromechanicalHoistExample
EXAMPLETITLE: Hydromechanical Hoist
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A hydromechanical hoist lifting a payload. An ideal hydraulic motor is driven by the pressure commanded by a controller. The controller estimates the current height of the payload by reading the angular velocity from the motor's flexible shaft. The rope is represented as a spring and damper, and the payload is modeled as a mass with gravitational force.


COMPONENT: sdl
EXAMPLENAME: WinchWithBrakeExample
EXAMPLETITLE: Winch with Brake
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A winch driven by a DC motor and controlled with a double-shoe brake. The motor is connected to a 24 volt supply, and the shaft speed is stepped down with a 10:1 gear reduction. The pulled load is modeled as a mass with sliding friction. At a simulation time of six seconds, force is applied to an internal double-shoe brake, stopping the winch.


COMPONENT: sdl
EXAMPLENAME: SuspensionSystemComparisonExample
EXAMPLETITLE: Suspension System Comparison
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A testbed containing three sets of springs and dampers excited by the same oscillating velocity source. The first uses the Shock Absorber block and includes linear stiffness and damping. Optional friction and hard stops are not used. The second shock absorber uses a Nonlinear Translational Spring and a Nonlinear Translational Damper specified by symmetric polynomials. The third uses a Variable Translational Spring and Variable Translational Damper. The spring constant is varied during the simulation using open loop control and the damping coefficient adjusts to ensure critical damping is achieved. Closed loop control can be added to simulate an adaptive suspension system.


COMPONENT: sdl
EXAMPLENAME: DoubleCardanJointExample
EXAMPLETITLE: Double Cardan Joint
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Two methods to create a constant rotational velocity output using universal joints. In the first method, the angle of the universal joints is exactly opposite. The output shaft axis is parallel to the input shaft axis, but offset by some distance.


COMPONENT: sdl
EXAMPLENAME: ManipulatorWithUnbalancedLoadExample
EXAMPLETITLE: Manipulator with Unbalanced Load
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A manipulator controlling the orientation of an end effector through an unbalanced arm. The motor is represented as a torque source using simple proportional control. The load on the end effector increases sharply when the end effector secures the load. Noise is introduced at each sensor to measure its effect on controller performance.


COMPONENT: sdl
EXAMPLENAME: DynamometerExample
EXAMPLETITLE: Dynamometer
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
This examples shows a dynamometer resisting a load from a prime mover. This prime mover is modeled as a torque source and could be an internal combustion engine, electric drive, or a hydraulic motor. The dyno absorbs input torque up to its limit, and allows rotation of connected loads for torques beyond. The dyno itself is modeled using the Fundamental Friction Clutch with static and dynamic limits set to the torque limit.


COMPONENT: sdl
EXAMPLENAME: CapstanWithSlipExample
EXAMPLETITLE: Capstan with Slip
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A capstan represented by a Belt Pulley block from the Simscape™ Driveline™ library. A 100-N tension applied to belt end B holds a variable load at end A in place, even as the load increases. When the load force increases past the friction limit, the belt slips. Increasing the friction by using a higher friction coefficient or wrap angle allows the pulley to hold an even greater load force. This example also shows how suddenly turning the capstan, starting at 3 seconds, causes momentary slip, which is quickly recovered.


COMPONENT: sdl
EXAMPLENAME: CompoundPulleyExample
EXAMPLETITLE: Compound Pulley
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A block and tackle system that is represented by the Belt Pulley and Cable blocks from the Simscape™ Driveline™ library. This compound pulley is rigged as a threefold purchase with two triple blocks. The system has a mechanical advantage of 6.


COMPONENT: sdl
EXAMPLENAME: FixedCaliperDiskBrakeExample
EXAMPLETITLE: Fixed Caliper Disk Brake
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Model, parameterize, and test a caliper disk brake. The example uses numerical data extracted from the tandem primary cylinder datasheet to identify an optimal design for the caliper disk brake. The example shows how to generate a compliance curve for the caliper disk brake.


COMPONENT: sdl
EXAMPLENAME: AutomotiveClutchExample
EXAMPLETITLE: Automotive Clutch
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Model, parameterize, and test an automotive clutch. Running the model plots the engine and transmission speed during a declutching scenario.


COMPONENT: sdl
EXAMPLENAME: TorqueConverterInTwoModeModelingExample
EXAMPLETITLE: Torque Converter in Two-Mode Modeling
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
Basic operations of a torque converter including lock-up clutch mechanism. You can select three different simulation cases - Basic Lock-up, Drive Mode Test, and Coast Mode Test.


COMPONENT: sdl
EXAMPLENAME: ThresholdParameterTuningExample
EXAMPLETITLE: Threshold Parameter Tuning
PRODUCT: MATLAB
DESCRIPTION:
Compare values for the Follower power threshold parameter in the Simple Gear block for a basic mechanical system. Blocks like the Simple Gear block use the tanh function when transitioning some physical characteristics between zero and nonzero. Threshold parameters like the Follower power threshold parameter are a numerical tool that you can use to aid the solver with transition and improve simulation performance. The appropriate value for this parameter depends on the system. You must determine it on a case by case basis by comparing simulation step sizes for a range of values, but the same advice applies to all threshold parameters.


COMPONENT: sdl
EXAMPLENAME: WindTurbineDrivelineWithVibrationsExample
EXAMPLETITLE: Wind Turbine Driveline with Vibrations
PRODUCT: MATLAB;Simulink;Simscape
DESCRIPTION:
A wind turbine rotor, controller, and flexible drive shaft with transverse vibrations. Click the button below to open the model.


COMPONENT: serdes
EXAMPLENAME: ModellingADCImpairmentsInSerDesReceiverExample
EXAMPLETITLE: Modelling ADC Impairments in SerDes Receiver
PRODUCT: MATLAB;SerDes Toolbox;Mixed-Signal Blockset
DESCRIPTION:
Model the effects of ADC Impairments, including offset error, gain error, and differences between interleaved ADCs on the performance of a SerDes Receiver. This example is based on the Architectural 112G PAM4 ADC Based SerDes Example, which explains the model as a whole, its purpose, and theory of operation in more detail.


COMPONENT: serdes
EXAMPLENAME: DesignIBISAMIModelsToSupportClockForwardingExample
EXAMPLETITLE: Design IBIS-AMI Models to Support Clock Forwarding
PRODUCT: MATLAB;SerDes Toolbox;Simulink;Signal Integrity Toolbox
DESCRIPTION:
Create Rx AMI models that support clock forwarding as defined in the IBIS 7.1 specification by modifying the library blocks in SerDes Toolbox™. This example will use a DDR5 write transfer (Controller to SDRAM) to demonstrate the setup.


COMPONENT: serdes
EXAMPLENAME: ArchitecturalDualSummingNodeExample
EXAMPLETITLE: Architectural 100G Dual-Summing-Node-DFE PAM4 SerDes Receiver Model
PRODUCT: MATLAB;SerDes Toolbox
DESCRIPTION:
The necessity of managing the adaptive loop update factors to ensure that the numerous adaptive loops don't fight against each other.


COMPONENT: serdes
EXAMPLENAME: ModelClockRecoveryLoopsInSerDesToolboxExample
EXAMPLETITLE: Model Clock Recovery Loops in SerDes Toolbox
PRODUCT: MATLAB;SerDes Toolbox;Mixed-Signal Blockset
DESCRIPTION:
Create detailed models of different types of serial channel clock recovery loops such as Alexander (bang-bang), Meuller-Muller, and Hogg & Chu.


COMPONENT: serdes
EXAMPLENAME: PCIe5TransmitterReceiverIBISAMIModelExample
EXAMPLETITLE: PCIe5 Transmitter/Receiver IBIS-AMI Model
PRODUCT: MATLAB;SerDes Toolbox
DESCRIPTION:
Create IBIS-AMI models for a PCI-Express Generation 5 (PCIe Gen5) transmitter and receiver using the library blocks in SerDes Toolbox™. The IBIS-AMI models generated by this example can be used in Serial Link Designer from Signal Integrity Toolbox™ and conform to the PCIe Gen5 Base-Specification published by the PCI-SIG.


COMPONENT: serdes
EXAMPLENAME: CustomizingSerDesToolboxDatapathControlSignalsExample
EXAMPLETITLE: Customizing SerDes Toolbox Datapath Control Signals
PRODUCT: MATLAB;SerDes Toolbox;Simulink
DESCRIPTION:
Customize the control signals in a SerDes system datapath by adding new custom AMI parameters and using MATLAB® function blocks. This allows you to customize existing control parameters without modifying the built-in blocks in the SerDes Toolbox™ library.


COMPONENT: serdes
EXAMPLENAME: SimulateCrosstalkCancelationInIBISAMIReceiverModelsExample
EXAMPLETITLE: Simulate Crosstalk Cancellation in IBIS AMI Receiver Models
PRODUCT: MATLAB;SerDes Toolbox
DESCRIPTION:
Simulate crosstalk cancellation in a SerDes Rx AMI model. You can disable crosstalk cancellation or select a specific aggressor column in the impulse_matrix to cancel. You can also replace the filter used in the example cancellationFilter.m with a CTLE that represents the filter implemented in the hardware.


COMPONENT: serdes
EXAMPLENAME: MeasureEyeOpeningsFromIntermediateSignalsExample
EXAMPLETITLE: Measure Eye Openings from Intermediate Signals in SerDes System Model
PRODUCT: MATLAB;SerDes Toolbox
DESCRIPTION:
Produce eye diagrams and related metrics for specific signals in a SerDes system using the Eye Measurement block.


COMPONENT: serdes
EXAMPLENAME: DesignIBISAMIModelsToSupportRxDecisionTimeExample
EXAMPLETITLE: Design IBIS-AMI Models to Support Rx Decision Time
PRODUCT: MATLAB;SerDes Toolbox;Simulink
DESCRIPTION:
Create Rx AMI models that support Rx Decision Time as defined in the IBIS (I/O Buffer Information Specification) version 7.1, by modifying the library blocks in SerDes Toolbox™. This example will use a typical SerDes Rx AMI model to demonstrate the setup.


COMPONENT: serdes
EXAMPLENAME: ManagingAMIParametersExample
EXAMPLETITLE: Managing AMI Parameters
PRODUCT: MATLAB;SerDes Toolbox;Simulink
DESCRIPTION:
Add, delete, modify, rename, and hide AMI parameters for an IBIS-AMI model built with SerDes Toolbox™. These AMI parameters are then available to be used with existing datapath blocks, user-created MATLAB® function blocks or optimization control loop, and can be passed to or returned from the AMI model executables (DLLs) created by SerDes Toolbox.


COMPONENT: shared_autoblks_mbc
EXAMPLENAME: EstEqCircuitLithiumIonBatteryDataExample
EXAMPLETITLE: Estimate Equivalent Circuit Lithium-Ion Battery Data
DESCRIPTION: Estimate data for an equivalent circuit lithium-ion polymer (LiPo) battery.
PRODUCT:
MATLAB;Model-Based Calibration Toolbox;Powertrain Blockset;Simulink Design Optimization;Optimization Toolbox;Curve Fitting Toolbox;Parallel Computing Toolbox;Simulink


COMPONENT: shared_gps
EXAMPLENAME: AddGPSSensorNoiseToGuidanceModelExample
EXAMPLETITLE: Add GPS Sensor Noise to Multirotor Guidance Model
PRODUCT: MATLAB;Simulink;UAV Toolbox
DESCRIPTION:
Use a GPS Block to add sensor noise to the position and velocity output of a guidance model in Simulink®.


COMPONENT: shared_ins
EXAMPLENAME: SimulateINSBlockExample
EXAMPLETITLE: Simulate INS Block
PRODUCT: MATLAB
DESCRIPTION:
Simulate an INS block by using the pose information of a vehicle undertaking a left-turn trajectory.


COMPONENT: shared_ins
EXAMPLENAME: GenerateINSMeasurementsFromDrivingScenarioInSimulinkExample
EXAMPLETITLE: Generate INS Measurements from Driving Scenario in Simulink
PRODUCT: MATLAB;Automated Driving Toolbox;Simulink
DESCRIPTION:
Generate measurements from an INS sensor that is mounted to a vehicle in a driving scenario. Visualize the position, velocity and acceleration profile of the vehicle using those sensor measurements in comparison with the ground truth values from the scenario.


COMPONENT: shared_mcb_soc_c2b
EXAMPLENAME: NetworkManagedDCDCPowerConverterExample
EXAMPLETITLE: Network Managed DC-DC Power Converter
PRODUCT:
Simulink;Simscape;Simscape Electrical;SoC Blockset;Embedded Coder;MATLAB;C2000 Microcontroller Blockset

DESCRIPTION:
Manage the asynchronous network commands to a high-speed, closed-loop DC-DC buck converter control algorithm executing the C2000 processor by using the Arm Cortex-M processor. In the TMS320F28388D and similar processor families, the C2000 processors execute the hard-realtime portions of the algorithm and use peripherals, such as ADC and PWM. In contrast, the Arm Cortex-M processor manages the high-level asynchronous communication, such as UDP or TCP, that connect the MCU to external systems. This example implements a technique that extends the DC-DC buck converter in the DC-DC Buck Converter on MCU example. You can apply this technique to any design in which a hard-realtime process executes on the C2000 MCU and a high-level asynchronous communication executes on the Arm Cortex-M processor.


COMPONENT: shared_mcb_soc_c2b
EXAMPLENAME: IntegrateMCUSchedulingAndPeripheralsInMotorControlExample
EXAMPLETITLE: Integrate MCU Scheduling and Peripherals in Motor Control Application
PRODUCT:
MATLAB;Embedded Coder;Motor Control Blockset;Simscape;Simscape Electrical;Simulink;C2000 Microcontroller Blockset

DESCRIPTION:
Identify and resolve issues with respect to peripheral settings and task scheduling early during development.


COMPONENT: shared_mcb_soc_c2b
EXAMPLENAME: GetStartedWithDualMotorDynoExample
EXAMPLETITLE: GetStartedWithDualMotorDynoExample
PRODUCT:
MATLAB;Embedded Coder;Motor Control Blockset;Simscape;Simscape Electrical;Simulink;SoC Blockset;C2000 Microcontroller Blockset


COMPONENT: shared_mcb_soc_c2b
EXAMPLENAME: PartitionMotorControlForMultiprocessorMCUsExample
EXAMPLETITLE: Partition Motor Control for Multiprocessor MCUs
PRODUCT:
MATLAB;Embedded Coder;Motor Control Blockset;Simscape;Simscape Electrical;Simulink;C2000 Microcontroller Blockset

DESCRIPTION:
Partition real-time motor control application on to multiple processors to achieve design modularity and improved control performance.


COMPONENT: shared_mcb_soc_c2b
EXAMPLENAME: ControlLawAcceleratorInDCDCPowerConversionExample
EXAMPLETITLE: Control Law Accelerator in DC-DC Power Conversion
PRODUCT: MATLAB;Simulink;Simscape;Simscape Electrical;Embedded Coder;C2000 Microcontroller Blockset
DESCRIPTION:
Manage the voltage mode control (VMC) algorithm for a closed loop DC-DC power conversion system by using the Control Law Accelerator (CLA). An auxiliary software current protection loop is managed by C2000 CPU. In the TMS320F28379D and similar processor families, the CLAs execute the hard-realtime portions of the algorithm can connect with hardware perhipherals such as ADC's and PWM's. The C2000 CPU is better suited for hard real-time portions of the algorithm that require multitasking, handling of asynchronous events, and communication with other cores. While this example extends the DC-DC buck converter developed in the DC-DC Buck Converter on MCU example, the strategy presented can be applied to any design where a resource intensive hard real-time process executes on the CLA and real-time multi-tasking processes run on C2000 CPU.


COMPONENT: shared_positioning
EXAMPLENAME: GenerateIMUReadingsOnADoublePendulumExample
EXAMPLETITLE: Generate IMU Readings on a Double Pendulum
PRODUCT: MATLAB
DESCRIPTION:
Generate inertial measurement unit (IMU) readings from two IMU sensors mounted on the links of a double pendulum. The double pendulum is modeled using Simscape Multibody™. For a step-by-step example of building a simple pendulum using Simscape Multibody™, see Model a Simple Pendulum.


COMPONENT: shared_positioning
EXAMPLENAME: IMUSensorFusionWithSimulinkExample
EXAMPLETITLE: IMU Sensor Fusion with Simulink
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Generate and fuse IMU sensor data using Simulink®. You can accurately model the behavior of an accelerometer, a gyroscope, and a magnetometer and fuse their outputs to compute orientation.


COMPONENT: shared_robotics_ros
EXAMPLENAME: SignFollowingRobotWithTimeSynchronizationROSGazeboExample
EXAMPLETITLE: Sign Following Robot with Time Synchronization Using ROS and Gazebo Co-Simulation
PRODUCT: MATLAB;Simulink;Robotics System Toolbox;ROS Toolbox
DESCRIPTION:
Use Simulink® to enable synchronized simulation between ROS and the Gazebo robot simulator using the Gazebo Pacer block.


COMPONENT: shared_robotics_ros
EXAMPLENAME: DesignAndSimulateAMobileManipulatorExample
PRODUCT: MATLAB;ROS Toolbox;Robotics System Toolbox
DESCRIPTION: Set up an end-to-end, pick-and-place workflow for a mobile manipulator using Simulink® and Gazebo®.
EXAMPLETITLE:
Design and Simulate Warehouse Pick-and-Place Application Using Mobile Manipulator in Simulink and Gazebo


COMPONENT: shared_robotics_ros
EXAMPLENAME: GenerateROSControlPluginFor3DShapeTracingManipulatorExample
EXAMPLETITLE: Generate Automated ros_control Plugin for 3-D Shape Tracing Manipulator
PRODUCT: MATLAB;Simulink;Robotics System Toolbox;ROS Toolbox;Computer Vision Toolbox
DESCRIPTION:
Generate and deploy a 3-D shape tracing contoller as a ros_control plugin from Simulink. Perform 3-D shape tracing using UR manipulator and depth point cloud.


COMPONENT: shared_scopes
EXAMPLENAME: SaveSimulationDataFromFloatingScopeExample
EXAMPLETITLE: Save Simulation Data from Floating Scope
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Save signals to the MATLAB® Workspace using a Floating Scope block. You can follow the same procedure to save data from a Scope Viewer. To save data from a Scope or Time Scope block, see Save Simulation Data Using Scope Block.


COMPONENT: shared_scopes
EXAMPLENAME: SaveSimulationDataUsingScopeBlockExample
EXAMPLETITLE: Save Simulation Data Using Scope Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Save signals to the MATLAB Workspace using the Scope block. You can us these steps for the Scope or Time Scope blocks. To save data from the Floating Scope or Scope viewer, see Save Simulation Data from Floating Scope (Simulink).


COMPONENT: shared_sdi
EXAMPLENAME: ViewEventBasedDataExample
EXAMPLETITLE: View Event-Based Data
PRODUCT: MATLAB;Simulink
DESCRIPTION:
You can log or import event data to the Simulation Data Inspector. In this example, the model SimpleMessagesModel logs signal data and message data using signal logging. For more information about the model, see Animate and Understand Sending and Receiving Messages.


COMPONENT: shared_sdi
EXAMPLENAME: ViewStringDataExample
EXAMPLETITLE: View String Data
PRODUCT: MATLAB;Simulink
DESCRIPTION:
You can log and view string data with your signal data in the Simulation Data Inspector. In the model stringData, the value of the sine wave block controls whether the switch sends a string reading Positive or Negative to the output. Open the model.


COMPONENT: shared_sdi
EXAMPLENAME: ViewComplexDataExample
EXAMPLETITLE: View Complex Data
PRODUCT: MATLAB
DESCRIPTION:
The complexSignal model logs two complex signals. The Complex Square Wave signal is logged using an Outport block. The Complex Sine Wave signal is logged using signal logging. Open the model.


COMPONENT: shared_sdi
EXAMPLENAME: PlotSimulationResultInSimulationDataInspectorExample
EXAMPLETITLE: Plot Simulation Result in Simulation Data Inspector
PRODUCT: MATLAB
DESCRIPTION:
You can use the Simulink.sdi.plot function to plot simulation results in the Simulation Data Inspector. Open the model vdp, which models the second-order Van der Pol differential equation. For more information about the model, see Van der Pol Oscillator.


COMPONENT: shared_sdi
EXAMPLENAME: ViewMultidimensionalDataExample
EXAMPLETITLE: View Multidimensional Data
PRODUCT: MATLAB;Simulink
DESCRIPTION:
You can view and analyze multidimensional signal data in the Simulation Data Inspector. To view a signal with multidimensional signal values, use the array plot. The model MultiDim contains six Sine Wave blocks, each vertically displaced from the previous sine wave by one, connected to a Mux block. Output from the Mux block is logged to the Simulation Data Inspector using an Outport block.


COMPONENT: shared_sl3d_robotics
EXAMPLENAME: GenerateStructuredTextCodeForShuttleAndRobotControlExample
EXAMPLETITLE: Generate Structured Text Code for Shuttle and Robot Control
PRODUCT: MATLAB;Robotics System Toolbox;Simulink;Simulink PLC Coder;Simulink 3D Animation;Stateflow
DESCRIPTION:
Generate and verify structured text code for the control system of a virtual assembly line that has two robotic work cells and a shuttle that goes between the robotic cells. The assembly line is based on a modular industrial framework created by ITQ GmbH known as Smart4i. This system consists of two robotic work cells that are connected by a shuttle track and a conveyor belt. One robot places cups onto the shuttle, and the other robot places balls in the cups. The control system is modeled using Stateflow®.


COMPONENT: shared_sl3d_robotics
EXAMPLENAME: AutomationOfVirtualAssemblyLineExample
EXAMPLETITLE: Automate Virtual Assembly Line with Two Robotic Workcells
PRODUCT:
MATLAB;Simulink 3D Animation;Robotics System Toolbox;Deep Learning Toolbox;Image Processing Toolbox;Computer Vision Toolbox

DESCRIPTION:
Simulation of an automated assembly to demonstrate virtual commissioning applications. The assembly line is based on a modular industrial framework created by ITQ GmbH known as Smart4i. This system consists of four components: two robotic workcells that are connected by a shuttle track and a conveyor belt. One of the two robots places cups onto the shuttle, while the other robot places balls in the cups. A slider then delivers those cups to a container. This simulation uses Stateflow® to control the system control and demonstrates how you can use Unreal Engine™ to simulate a complete virtual commissioning application in Simulink®. For an example showing how to deploy the main logic in Stateflow using Simulink PLC Coder™, see Generate Structured Text Code for Shuttle and Robot Control.


COMPONENT: shared_soc_visionhdl
EXAMPLENAME: YOLOv2VehicleDetectorOnSoCExample
EXAMPLETITLE: Integrate YOLO v2 Vehicle Detector System on SoC
PRODUCT: Vision HDL Toolbox;MATLAB;Simulink;Computer Vision Toolbox;Deep Learning Toolbox
DESCRIPTION:
Simulate a YOLO v2 vehicle detection algorithm that contains FPGA and ARM sections for deployment to an SoC device.


COMPONENT: shared_soc_visionhdl
EXAMPLENAME: DeployAndVerifyYOLOV2VehicleDetectorOnFPGAExample
EXAMPLETITLE: Deploy and Verify YOLO v2 Vehicle Detector on FPGA
PRODUCT: Vision HDL Toolbox;Deep Learning HDL Toolbox;Computer Vision Toolbox;Simulink;HDL Coder
DESCRIPTION:
Deploy a you only look once (YOLO) v2 vehicle detector on FPGA and verify the end-to-end application using MATLAB®.


COMPONENT: shared_soc_visionhdl
EXAMPLENAME: ImageNormalizationWithExternalMemoryExample
EXAMPLETITLE: Image Normalization Using External Memory
PRODUCT: Simulink;Vision HDL Toolbox;SoC Blockset;Fixed-Point Designer;HDL Coder
DESCRIPTION:
Normalize image pixel values using external memory. The example includes two models that show two ways to model the external memory: SoC external memory modeling and behavioral memory modeling. The example also verifies that the results of the two memory models are the same.


COMPONENT: shared_soc_visionhdl
EXAMPLENAME: CLAHEExtMemExample
EXAMPLETITLE: Contrast Limited Adaptive Histogram Equalization with External Memory
PRODUCT: MATLAB;HDL Coder;SoC Blockset;Vision HDL Toolbox;Simulink;Fixed-Point Designer
DESCRIPTION:
Implement the contrast-limited adaptive histogram equalization (CLAHE) algorithm for FPGA, including an external memory interface.


COMPONENT: shared_soc_visionhdl
EXAMPLENAME: DebugYOLOV2VehicleDetectorOnFPGAExample
EXAMPLETITLE: Debug YOLO v2 Vehicle Detector on FPGA
PRODUCT:
Deep Learning HDL Toolbox;HDL Coder;Simulink;Computer Vision Toolbox;Vision HDL Toolbox;HDL Verifier;DSP System Toolbox

DESCRIPTION:
Debug a vehicle detector design by viewing internal signals while the design is deployed on a board.


COMPONENT: shared_soc_visionhdl
EXAMPLENAME: YOLOV2VehicleDetectorWithLiveCameraInputOnZynqBasedHWExample
EXAMPLETITLE: YOLO v2 Vehicle Detector with Live Camera Input on Zynq-Based Hardware
PRODUCT:
MATLAB;Vision HDL Toolbox;Deep Learning HDL Toolbox;HDL Coder;Computer Vision Toolbox;Simulink;Deep Learning Toolbox;Embedded Coder

DESCRIPTION:
Deploy a YOLO v2 vehicle detection algorithm to the FPGA and ARM processor on an SoC device and process live HDMI video input.


COMPONENT: shared_uav_nvidia
EXAMPLENAME: StreamCameraDepthLabelDataFromUnrealToJetsonExample
EXAMPLETITLE: Stream Camera, Depth and Semantic Segmentation Data from Unreal Engine to NVIDIA Jetson
PRODUCT: MATLAB;Simulink;UAV Toolbox;Simulink 3D Animation
DESCRIPTION:
Stream simulated camera, depth, and semantic segmentation label data from an Unreal Engine® scene to NVIDIA® Jetson™ hardware using the Video Send block in Simulink®. It then shows how to visualize incoming data streams on a monitor connected to the Jetson platform, by deploying separate models for each incoming data stream. The deployed models contain the Network Video Receive and SDL Video Display blocks from the MATLAB® Coder™ Support Package for NVIDIA Jetson and NVIDIA DRIVE® Platforms.


COMPONENT: shared_uav_nvidia
EXAMPLENAME: OnboardCompPathPlanningPX4SITLDeployableNVIDIAJetsonExample
EXAMPLETITLE: Onboard Computer Path Planning Interface for PX4 SITL Deployable on NVIDIA Jetson
PRODUCT: MATLAB;UAV Toolbox;Simulink
DESCRIPTION:
Demonstrates enabling and interfacing onboard computer path planning with PX4® Software-in-the-Loop (SITL).


COMPONENT: shared_vision_driving
EXAMPLENAME: VisualLocalizationInAParkingLotExample
EXAMPLETITLE: Visual Localization in a Parking Lot
PRODUCT: Automated Driving Toolbox;Computer Vision Toolbox;Simulink
DESCRIPTION:
Develop a visual localization system using synthetic image data from a parking lot scene in Unreal Engine environment.


COMPONENT: shared_vision_driving
EXAMPLENAME: SelectWaypointsFor3DSimulationExample
EXAMPLETITLE: Select Waypoints for Unreal Engine Simulation
PRODUCT: MATLAB;Automated Driving Toolbox;Simulink;Image Processing Toolbox;Simulink 3D Animation
DESCRIPTION:
Select waypoints from a scene and visualize the path of a vehicle following these waypoints in the Unreal Engine simulation environment.


COMPONENT: shared_vision_driving
EXAMPLENAME: DesignLidarSLAMAlgorithmUsing3DSimulationEnvironmentExample
EXAMPLETITLE: Design Lidar SLAM Algorithm Using Unreal Engine Simulation Environment
PRODUCT: MATLAB;Automated Driving Toolbox;Computer Vision Toolbox;Navigation Toolbox;Simulink
DESCRIPTION:
Develop a simultaneous localization and mapping algorithm using synthetic lidar sensor data recorded from the Unreal Engine simulation environment.


COMPONENT: shared_vision_driving
EXAMPLENAME: DevelopVisualSLAMAlgorithmUsingUnrealEngineSimulationExample
EXAMPLETITLE: Develop Visual SLAM Algorithm Using Unreal Engine Simulation
PRODUCT: MATLAB;Simulink;Automated Driving Toolbox;Computer Vision Toolbox;Navigation Toolbox
DESCRIPTION:
Develop a visual simultaneous localization and mapping (SLAM) algorithm using image data from the Unreal Engine simulation environment.


COMPONENT: shared_vision_driving
EXAMPLENAME: LidarLocalizationInUnrealExample
EXAMPLETITLE: Lidar Localization with Unreal Engine Simulation
PRODUCT: MATLAB;Automated Driving Toolbox;Computer Vision Toolbox;Image Processing Toolbox;Simulink
DESCRIPTION:
Develop and evaluate a lidar localization algorithm using synthetic lidar data from the Unreal Engine simulation environment.


COMPONENT: shared_vnv
EXAMPLENAME: RunFaultInjectionTestsExample
EXAMPLETITLE: Run Fault Injection Tests on an Example Model
PRODUCT: MATLAB;Simulink;Simulink Fault Analyzer;Simulink Test;Stateflow
DESCRIPTION:
Run tests that activate and inject faults by using fault sets. After you inject faults, you can assess the signals and determine if the faults caused the desired outputs by using temporal assessments.


COMPONENT: signal
EXAMPLENAME: SFDRMeasurementExample
EXAMPLETITLE: Spurious-Free Dynamic Range (SFDR) Measurement
PRODUCT: MATLAB;Signal Processing Toolbox;Simulink
DESCRIPTION:
Measure the SFDR of a numerically controlled oscillator and explore the effects of adding phase dither.


COMPONENT: sim3d
EXAMPLENAME: ViewSemanticSegmentationAndVisionDetectionInRRSceneExample
EXAMPLETITLE: Import RoadRunner Scene into Unreal Engine Using Simulink
PRODUCT:
MATLAB;Simulink 3D Animation;Simulink;Automated Driving Toolbox;Computer Vision Toolbox;Image Processing Toolbox

DESCRIPTION:
Import a scene built in RoadRunner into an Unreal Engine simulation in Simulink to generate vision detections and ground-truth semantic segmentation labels for the scene.


COMPONENT: simevents
EXAMPLENAME: GenerateMultipleEntitiesExample
EXAMPLETITLE: A Simple Example of Generating Multiple Entities
PRODUCT: MATLAB;SimEvents
DESCRIPTION:
In this example, you can simultaneously generate multiple entities at the start of the simulation. You can then observe the behavior of the model from the output of the Dashboard Scope block.


COMPONENT: simevents
EXAMPLENAME: StarRoutingExample
EXAMPLETITLE: Distributing Multi-Class Jobs to Service Stations
PRODUCT: MATLAB;SimEvents;Simulink
DESCRIPTION:
Model a central resource that manages distributed processing according to an explicit formula. The example describes a distribution center that manages a series of processes that each job undergoes, with each job carrying information about the series of processes that it must undergo. One of the applications where this could be useful is when you want to model a central dispatcher that routes calls from one call processing station to another.


