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
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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.
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