Evaluate fuzzy inference system and view rules
Fuzzy Logic Toolbox
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.
101 points for discretizing output variable
Interpreted execution simulation
Does not have additional output ports for accessing intermediate fuzzy inference results.
Refresh rate— Time between rule viewer updates
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.
|Type: string, character vector|
Warns starting in R2019b
Support for representing fuzzy inference systems as structures will be removed in a future
instead. There are differences between these representations that require updates to your
code. These differences include:
Object property names that differ from the corresponding structure fields.
Objects store text data as strings rather than as character vectors.
Also, all Fuzzy Logic Toolbox™ functions that accepted or returned fuzzy inference systems as structures now
accept and return either
To convert existing fuzzy inference system structures to objects, use the
Usage notes and limitations:
Generating code using the Fuzzy Logic Controller with Ruleviewer block produces the same code as using the Fuzzy Logic Controller block. However, the Fuzzy Logic Controller with Ruleviewer block does not support:
Generating code for single-point or fixed-point data.
Changing the number of samples for discretizing the output variable range.