MATLAB Fuzzy Controller Implementation with Gaussian Membership Functions

This is a MATLAB programming file implementing a fuzzy controller with Gaussian membership functions! The file contains detailed explanations and sample code demonstrating how to program a fuzzy controller. Fuzzy controllers are control methods based on fuzzy logic that generate fuzzy outputs according to input variables' fuzzy sets and rule bases. The implementation typically involves defining membership functions, creating fuzzy rules, and implementing inference mechanisms. Through fuzzy controllers, we can achieve precise control of complex systems, with particularly excellent performance for problems involving significant uncertainty or fuzziness. In this programming file, we use Gaussian membership functions to define fuzzy sets, characterized by their smooth bell-shaped curves and mathematical expression: μ(x) = exp(-(x-c)²/(2σ²)), where c represents the center and σ controls the width. The controller processes inputs through fuzzy inference systems (FIS) including fuzzification, rule evaluation, aggregation, and defuzzification stages. Key implementation aspects covered include: - Gaussian MF parameter configuration (center and spread values) - Fuzzy rule base construction using linguistic variables - Mamdani or Sugeno inference system implementation - Defuzzification methods (centroid, bisector, MOM) - MATLAB Fuzzy Logic Toolbox functions: addvar(), addmf(), addrule() If you're interested in fuzzy controller programming or want to learn more about fuzzy control systems, this programming file will be valuable for understanding both theoretical concepts and practical MATLAB implementation techniques!