Fuzzy PID Control for DC Motor

This research presents a fuzzy PID control system for DC motor applications, developed as part of my graduation project. The study provides an in-depth investigation of fuzzy control methodologies, featuring detailed algorithm comparisons and performance analyses. The implementation explores various fuzzy control strategies including Mamdani and Sugeno-type inference systems, with MATLAB/Simulink code demonstrating real-time parameter tuning through fuzzy logic controllers. Key aspects covered include: membership function design for error and error-rate inputs, rule-base establishment for PID gain adjustment, and defuzzification methods for control output generation. The research examines practical applications in DC motor speed and position control, proposing enhancements such as adaptive rule bases and hybrid fuzzy-PID structures. All algorithms are implemented with commented code sections showing PID gain calculation methods (Kp, Ki, Kd optimization through fuzzy inference) and real-time response visualization. This work aims to provide valuable reference material for future researchers and contribute to advancements in intelligent control systems.