Fuzzy Logic Toolbox™ provides MATLAB® functions, apps, 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 stand-alone 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.
To illustrate the value of fuzzy logic, examine both linear and fuzzy approaches to a basic tipping problem.
Interactively construct a fuzzy inference system using the Fuzzy Logic Designer app.
Construct a fuzzy inference system at the MATLAB command line.
Fuzzy logic uses linguistic variables, defined as fuzzy sets, to approximate human reasoning.
A fuzzy logic system is a collection of fuzzy if-then rules that perform logical operations on fuzzy sets.
Fuzzy inference maps an input space to an output space using a series of fuzzy if-then rules.
Display the membership functions supported by Fuzzy Logic Toolbox software.
Compare the defuzzification methods supported by Fuzzy Logic Toolbox software.
You can implement either Mamdani or Sugeno fuzzy inference systems using Fuzzy Logic Toolbox software.