Simulink Simulation of a Simple Fuzzy Controller

This project demonstrates a Simulink simulation of a simple fuzzy logic controller (FLC). A fuzzy controller operates on fuzzy logic principles, handling imprecise relationships between inputs and outputs through linguistic variables and rule-based inference. The simulation constructs a basic FLC architecture within Simulink, implementing key components: fuzzification modules to convert crisp inputs into membership functions, a rule base containing IF-THEN statements, an inference engine for decision-making, and defuzzification methods (like centroid or Mamdani) to generate precise output signals. Through this simulation, users can observe how the controller processes fuzzy input values to produce corresponding control outputs, demonstrating real-time system regulation. The implementation allows parameter adjustment of membership function ranges, rule weights, and defuzzification techniques to analyze different control behaviors. This hands-on approach provides an intuitive understanding of fuzzy controller fundamentals, including rule evaluation workflows and stability analysis through response curve visualization.