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Fuzzy Inference System Modeling

Build Mamdani and Sugeno fuzzy inference systems

Fuzzy inference is the process of formulating input/output mappings using fuzzy logic. Fuzzy Logic Toolbox™ software provides command-line functions and an app for creating Mamdani and Sugeno fuzzy systems. For more information on fuzzy logic, see What Is Fuzzy Logic? For more information on fuzzy inference, see Fuzzy Inference Process.


Fuzzy Logic Designer Design and test fuzzy inference systems


newfis Create new Fuzzy Inference System
genfis1 Generate Fuzzy Inference System structure from data using grid partition
genfis2 Generate Fuzzy Inference System structure from data using subtractive clustering
genfis3 Generate Fuzzy Inference System structure from data using FCM clustering
addvar Add variable to Fuzzy Inference System
rmvar Remove variables from fuzzy inference system
mam2sug Transform Mamdani Fuzzy Inference System into Sugeno Fuzzy Inference System
getfis Get fuzzy system properties
setfis Set fuzzy system properties
mfedit Open Membership Function Editor
addmf Add membership function to Fuzzy Inference System
rmmf Remove membership function from fuzzy inference system
ruleedit Open Rule Editor
ruleview Open Rule Viewer
addrule Add rule to Fuzzy Inference System
showrule Display Fuzzy Inference System rules
parsrule Parse fuzzy rules
evalfis Perform fuzzy inference calculations
plotfis Plot Fuzzy Inference System
surfview Open Surface Viewer
gensurf Generate Fuzzy Inference System output surface
showfis Display annotated Fuzzy Inference System
readfis Load Fuzzy Inference System from file
writefis Save Fuzzy Inference System to file
gaussmf Gaussian curve membership function
gbellmf Generalized bell-shaped membership function
trimf Triangular-shaped membership function
dsigmf Difference between two sigmoidal functions membership function
gauss2mf Gaussian combination membership function
pimf Π-shaped membership function
psigmf Product of two sigmoidal membership functions
sigmf Sigmoidal membership function
smf S-shaped membership function
trapmf Trapezoidal-shaped membership function
zmf Z-shaped membership function
plotmf Plot all membership functions for given variable
evalmf Generic membership function evaluation
mf2mf Translate parameters between membership functions
defuzz Defuzzify membership function
probor Probabilistic OR
fuzarith Perform fuzzy arithmetic


Fuzzy Logic Basics

What Is Fuzzy Logic?

Fuzzy logic uses linguistic variables, defined as fuzzy sets, to approximate human reasoning.

Foundations of Fuzzy Logic

A fuzzy logic system is a collection fuzzy if-then rules that perform logical operations on fuzzy sets.

Fuzzy Inference

Fuzzy Inference Process

Fuzzy inference maps an input space to an output space using a series of fuzzy if-then rules.

What Is Mamdani-Type Fuzzy Inference?

In Mamdani systems, the output of each if-then rule is a fuzzy set. To determine a crisp output value, these fuzzy sets are aggregated and defuzzified.

What Is Sugeno-Type Fuzzy Inference?

In Sugeno systems, the output of each if-then rule is either constant or a linear function of the input variables. The final output value is the weighted average of all rule outputs.

Comparison of Sugeno and Mamdani Systems

Both Mamdani and Sugeno systems have several advantages depending on your specific application.

Build Fuzzy Inference Systems

Build Mamdani Systems Using Fuzzy Logic Designer

Interactively construct a Mamdani fuzzy inference system using the Fuzzy Logic Designer app.

Build Mamdani Systems at the Command Line

Construct a Mamdani fuzzy inference system at the MATLAB® command line.

Build Mamdani Systems Using Custom Functions

You can replace the built-in membership functions and fuzzy inference functions with your own custom functions.

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