Fuzzy Logic Toolbox0 pages

Fuzzy Logic Toolbox

Design and simulate fuzzy logic systems

Fuzzy Logic Toolbox™ provides MATLAB functions, graphical tools, and a Simulink block for analyzing,

designing, and simulating systems based on fuzzy logic. The product guides you through the steps of designing

fuzzy inference systems. Functions are provided for many common methods, including fuzzy clustering and

adaptive neurofuzzy learning.

The toolbox lets you model complex system behaviors using simple logic rules and then implement these rules in

a fuzzy inference system. You can use it as a standalone fuzzy inference engine. Alternatively, you can use fuzzy

inference blocks in Simulink and simulate the fuzzy systems within a comprehensive model of the entire dynamic

system.

Key Features

Specialized GUIs for building fuzzy inference systems and viewing and analyzing results

Membership functions for creating fuzzy inference systems

Support for AND, OR, and NOT logic in user-defined rules

Standard Mamdani and Sugeno-type fuzzy inference systems

Automated membership function shaping through neuroadaptive and fuzzy clustering learning techniques

Ability to embed a fuzzy inference system in a Simulink model

Ability to generate embeddable C code or stand-alone executable fuzzy inference engines

^slcp

File Edit View Display Diagram Simulation Analysis Code Tools Help

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Target Position

Constant

Target Position

(Jrfo use-Driven)

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I Animation

T * MUX _jn

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Carta Pole

Dynamics

Fuzzy Logic

Controller

Balancing a pole on a moving cart. The system, which is similar to an inverted pendulum, uses a Fuzzy Controller block within

Simulink to balance the pole.

^VMathWorks-

Accelerating the pace of engineering and science

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