Fuzzy Logic Designer
Design, test, and tune fuzzy inference systems
The Fuzzy Logic Designer app lets you design, test, and tune a fuzzy inference system (FIS) for modeling complex system behavior.
Using this app, you can:
Design Mamdani and Sugeno FISs.
Design type-1 and type-2 FISs.
Tune the rules and membership functions of a FIS or FIS tree.
Design and tune FIS trees. (since R2023b)
Analyze the behavior of a fuzzy system, including:
View rule inference process for given input values
View output surface maps for fuzzy inference systems.
Compare FIS outputs with corresponding output values from testing data. (since R2023a)
View error distributions across input ranges based on testing data. (since R2023a)
Export FIS designs to the MATLAB® workspace.
Open the Fuzzy Logic Designer App
MATLAB Toolstrip: On the Apps tab, under Control System Design and Analysis, click the app icon.
MATLAB command prompt: Enter
Import FIS from Workspace
In Fuzzy Logic Designer, under Import > Import Fuzzy Inference System from Workspace, click a FIS or FIS tree.
A new Fuzzy Logic Designer instance opens and loads the selected FIS.
Import FIS from File
In Fuzzy Logic Designer, select Import > Import Fuzzy Inference System from File.
Then, in the Import Fuzzy Inference System dialog box, select a FIS or MAT file and click Open.
Using Fuzzy Logic Designer, you can convert between Mamdani and Sugeno systems and between type-1 and type-2 systems.
When you convert a FIS, the app adds the converted FIS to the Design Browser. To make the converted system active, select it in the Design Browser and click Set Active Design.
For more information on converting between Mamdani and Sugeno systems, see Mamdani and Sugeno Fuzzy Inference Systems.
- Get Started Using Fuzzy Logic Designer
- Build Fuzzy Systems Using Fuzzy Logic Designer
- Build FIS Tree Using Fuzzy Logic Designer
- Define Fuzzy Rules Using Fuzzy Logic Designer
- Define Membership Functions Using Fuzzy Logic Designer
- Analyze Fuzzy System Using Fuzzy Logic Designer
- Tune Fuzzy Inference System Using Fuzzy Logic Designer
- Tune FIS Tree Using Fuzzy Logic Designer
- Train Adaptive Neuro-Fuzzy Inference Systems
- Configure Tuning Options in Fuzzy Logic Designer
- Select Rules and Parameters to Tune in Fuzzy Logic Designer
- Export FIS and Simulation Data from Fuzzy Logic Designer
fuzzyLogicDesigner opens the Fuzzy Logic Designer app and
loads the Getting Started dialog box, where you can open an existing FIS or create
an initial FIS structure. For more information, see Get Started Using Fuzzy Logic Designer.
fuzzyLogicDesigner( opens the app and loads the
fuzzy inference system
fis can be any
sugfistype2 object in
the MATLAB workspace.
fuzzyLogicDesigner( opens the app and loads
a fuzzy inference system from a file.
fileName is the name of a
*.fis) file on the MATLAB path.
To save a fuzzy inference system to a FIS file:
In Fuzzy Logic Designer, under Save, select the fuzzy inference system.
At the command line, use
Version HistoryIntroduced in R2014b
R2023b: Design, tune, and analyze FIS trees
R2023b: Tunable parameter selections stored with each FIS design
When tuning FIS designs in Fuzzy Logic Designer, tunable parameter selections are now stored separately for each design. Previously, the app maintained a single set of tunable parameters for each app session.
R2023a: Tune rules and membership functions
You can interactively tune the rules and membership function parameters of the following types of fuzzy inference systems.
Mamdani and Sugeno systems
Type-1 and type-2 systems
For an example, see Tune Fuzzy Inference System Using Fuzzy Logic Designer.
R2023a: Interactively evaluate performance of FIS using testing data
You can interactively evaluate the performance of fuzzy inference system designs for given input/output testing data using the following documents in the app.
System Validation — Compare the outputs from each FIS design with the corresponding output value from the testing data.
Error Distribution — For a given FIS design, view the output error for different combinations of inputs.
For more information on analyzing FIS designs, see Analyze Fuzzy System Using Fuzzy Logic Designer.
R2023a: Automatically distribute membership functions across variable range
When defining membership functions for input and output variables, you can evenly distribute existing membership function across the variable range. For more information on defining membership functions, see Define Membership Functions Using Fuzzy Logic Designer.
R2022b: Redesigned Fuzzy Logic Designer app
The redesigned app streamlines workflows for interactively building fuzzy inference systems. Using the updated app, you can:
Design both Mamdani and Sugeno fuzzy inference systems
Design fuzzy inference systems with either type-1 or type-2 membership functions
R2019b: Support for fuzzy inference system structures will be removed
Support for representing fuzzy inference systems as structures will be removed in
a future release. Use
objects with this function instead. To convert existing fuzzy inference system
structures to objects, use the
This change was announced in R2018b. Using fuzzy inference system structures with this app issues a warning starting in R2019b.
R2014b: Command to open app renamed to
Previously, the command to open the app was