Nonlinear ARX Model
Simulate nonlinear ARX model in Simulink software
- Library:
System Identification Toolbox / Models
Description
The Nonlinear ARX Model block simulates the output of a nonlinear ARX
model using time-domain input data. The model is an idnlarx model that you previously estimated or constructed in the
MATLAB® workspace. You specify initial conditions for the simulation as either
steady-state input and output signal levels or as an initial state vector.
Ports
Input
Port_1(In1) — Simulation input data
scalar | vector
Simulation input data, specified as a scalar for a single-input model. The data must be time-domain data. For multi-input models, specify the input as an Nu-element vector, where Nu is the number of inputs. For example, you can use a Vector Concatenate block to concatenate scalar signals into a vector signal.
Note
Do not use a Bus Creator or Mux block to produce the vector signal.
Data Types: double
Output
Port_1(Out1) — Simulated output
scalar | vector
Simulated output from nonlinear ARX model, returned as a scalar for a single-output model and an Ny-element vector for a model with Ny outputs.
Data Types: double
Parameters
Model — Nonlinear ARX model to be simulated
idnlarx object
Nonlinear ARX model to be simulated, specified as an
idnlarx object. You previously estimate or
construct the idnlarx model in the MATLAB workspace.
Initial conditions — Initial condition specification for simulation
Input and output values (default) | State values
The states of a nonlinear ARX model correspond to the dynamic elements of
the nonlinear ARX model structure. The dynamic elements are the model
regressors. Regressors can be the delayed input or output variables
(standard regressors) or user-defined transformations of delayed
input-output variables (custom regressors). For more information about the
states of a nonlinear ARX model, see the idnlarx reference
page.
For simulating nonlinear ARX models, you can specify the initial conditions one of the following:
Input and output values— Specify steady-state input and output signal levels inInput levelandOutput level, respectively.State values— Specify a vector of length equal to the number of states in the model inSpecify initial states as a vector.
Input level — Steady-state input signal level
0 (default) | scalar
Steady-state input signal level before simulation, specified as a scalar.
Dependency
To enable this parameter, specify Initial
conditions as Input and output
values.
Output level — Steady-state output signal level
0 (default) | scalar
Steady-state output signal level before simulation, specified as a scalar.
Dependency
To enable this parameter, specify Initial
conditions as Input and output
values.
Specify initial states as a vector — Initial state values
0 (default) | vector
Initial state values of the model, specified as an
Nx-element vector, where Nx is the
number of states of the model. This parameter is named Vector of
state values until you specify
Model.
If you do not know the initial states, you can estimate these states as follows:
To simulate the model around a given input level when you do not know the corresponding output level, estimate the equilibrium state values using the
findopcommand. For example, to simulate a modelMabout a steady-state point where the input is1and the output is unknown, specify the initial state values asX0, whereX0 = findop(M,'steady',1,NaN)To estimate the initial states that provide a best fit between measured data and the simulated response of the model for the same input, use the
findstatescommand. For example, to compute initial states such that the response of the modelMmatches the output data in the data setz, specifyX0, such that:X0 = findstates(M,z,Inf)
To continue a simulation from a previous simulation run, use the simulated input-output values from the previous simulation to compute the initial states
X0for the current simulation. Use thedata2statecommand to computeX0. For example, suppose thatfirstSimDatais a variable that stores the input and output values from a previous simulation. For a modelM, you can specifyX0, such that:X0 = data2state(M,firstSimData)
Dependency
To enable this parameter, specify Initial
conditions as State
values.
