Fuzzy Logic Controller with Ruleviewer

Evaluate fuzzy inference system and view rules

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  • Library:

  • Fuzzy Logic Toolbox

  • Fuzzy Logic Controller with Ruleviewer block

Description

The Fuzzy Logic Controller with Ruleviewer block implements a fuzzy inference system (FIS) in Simulink® and displays the fuzzy inference process in the Rule Viewer during the simulation. You specify the FIS to evaluate using the FIS matrix parameter. To change the time between Rule Viewer updates, specify the Refresh rate in seconds.

For more information on fuzzy inference, see Fuzzy Inference Process.

The Fuzzy Logic Controller with Ruleviewer block does not support all the features supported by the Fuzzy Logic Controller block. The Fuzzy Logic Controller with Ruleviewer block:

  • Only supports double-precision data.

  • Uses 101 points for discretizing output variable ranges.

  • Only supports Interpreted execution simulation mode.

  • Does not have additional output ports for accessing intermediate fuzzy inference results.

Ports

Input

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For a single-input fuzzy inference system, the input is a scalar. For a multi-input fuzzy system, combine the inputs into a vector signal using blocks such as:

Output

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For a single-output fuzzy inference system, the output is a scalar. For a multi-output fuzzy system, the output is a vector. To split system outputs into scalar signals, use the Demux (Simulink) block.

Parameters

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Fuzzy inference system to evaluate, specified as a mamfis or sugfis object. Specify the name of a FIS object in the MATLAB® workspace.

Programmatic Use

Block Parameter: fismatrix
Type: string, character vector
Default: "fis"

Time between rule viewer updates in seconds, specified as a scalar. During simulation, the Rule Viewer display updates at the specified rate to show the inference process for the latest input signal values.

Programmatic Use

Block Parameter: Ts
Type: string, character vector
Default: "2"

Model Examples

Simulate Fuzzy Inference System

Simulate Fuzzy Inference System

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.

Open Script

Compatibility Considerations

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Warns starting in R2019b

Extended Capabilities

See Also

Blocks

Apps

Functions

Topics

Introduced before R2006a

Fuzzy Logic Toolbox Documentation

Support