Get Started with Fuzzy Logic Toolbox
Fuzzy Logic Toolbox™ provides MATLAB® functions, apps, and a Simulink® block for analyzing, designing, and simulating fuzzy logic systems. The product lets you specify and configure inputs, outputs, membership functions, and rules of type-1 and type-2 fuzzy inference systems.
The toolbox lets you automatically tune membership functions and rules of a fuzzy inference system from data. You can evaluate the designed fuzzy logic systems in MATLAB and Simulink. Additionally, you can use the fuzzy inference system as a support system to explain artificial intelligence (AI)-based black-box models. You can generate standalone executables or C/C++ code and IEC 61131-3 Structured Text to evaluate and implement fuzzy logic systems.
- Fuzzy vs. Nonfuzzy Logic
To illustrate the value of fuzzy logic, examine both linear and fuzzy approaches to a basic tipping problem.
- Build Fuzzy Systems Using Fuzzy Logic Designer
Interactively construct a fuzzy inference system using the Fuzzy Logic Designer app.
- Build Fuzzy Systems at the Command Line
Construct a fuzzy inference system at the MATLAB command line.
About Fuzzy Logic
- 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 of fuzzy if-then rules that perform logical operations on fuzzy sets.
- Mamdani and Sugeno Fuzzy Inference Systems
You can implement either Mamdani or Sugeno fuzzy inference systems using Fuzzy Logic Toolbox software.
- Fuzzy Inference Process
Fuzzy inference maps an input space to an output space using a series of fuzzy if-then rules.
- Defuzzification Methods
Compare the defuzzification methods supported by Fuzzy Logic Toolbox software.