What Is 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.
Published: 9 Mar 2023
Fuzzy Logic Toolbox lets you design, analyze, and evaluate complex controls and decision making systems using fuzzy logic. The toolbox also lets you automatically tune membership functions and rules of a fuzzy inference system directly from data. You can interactively design and evaluate different types of fuzzy inference systems, including Type 2 Mamdani and Sugeno systems, using the Fuzzy Logic Designer app.
You can define the number of inputs and outputs, configure the membership functions for each of the inputs and outputs, and create if-then rules to capture the behavior of your system. Once designed, you can evaluate the performance of your fuzzy system across different scenarios using the rule viewer, and infer the overall mapping of inputs and outputs using the control surface.
In situations when you do not have expert knowledge of your system, but have collection of input and output data that you would like to use for modeling, you can automatically tune membership functions and rules of your fuzzy inference system directly from data. You can leverage techniques such as genetic algorithms and particle swarm optimization from Global Optimization Toolbox, or use the neuroadaptive learning techniques to tune your fuzzy system.
You can also use the Tune Fuzzy Inference system as a support system to explain AI-based black box models. You can model complex systems with large number of inputs and outputs as a collection of smaller, interconnected fuzzy inference systems using fuzzy trees. You can simulate and test your fuzzy inference system in a system level simulation model in Simulink using built-in blocks.
With the co-generation products you can generate C, C++, and IEC 61131 structured text code to implement your fuzzy inference system in embedded devices and PLCs. You can also deploy your fuzzy system as a standalone executable using MATLAB Compiler. For more information on Fuzzy Logic Toolbox return to the product page or check out the examples from our documentation.