Fuzzy Control Algorithm Implementation with MATLAB Source Code

This source code provides a MATLAB implementation of fuzzy control algorithms, covering essential components such as fuzzy modeling of controlled systems, transformation of input variables to appropriate discourse domains, and establishment of comprehensive fuzzy rule bases. The implementation demonstrates how to define membership functions using MATLAB's Fuzzy Logic Toolbox functions like addvar and addmf, and shows practical methods for converting raw input data into normalized discourse domains through scaling techniques. For fuzzy rule base development, the code illustrates rule creation using conditional statements and rule weighting mechanisms. Beyond the core implementation, the code includes functionality for performance optimization of fuzzy controllers, such as adjusting fuzzy rule weights and enhancing fuzzy inference methods through different implication and aggregation operators. The implementation also explores practical applications where fuzzy control can be integrated with other control strategies like PID or neural networks to achieve superior control performance. The code provides a complete framework for fuzzy control algorithm implementation using MATLAB's fuzzy logic toolbox functions, featuring clear modular structure that allows for straightforward extensions and improvements. The architecture supports customization of membership functions, rule bases, and inference parameters, offering significant potential for further development and adaptation to specific control applications.