Simulation Study of Fuzzy Self-Tuning PID Control for DC Motor Speed with Disturbance Rejection

DC motors are widely used in industrial drive systems due to their simple structure, ease of control, and reliable speed regulation. However, the performance of conventional PID controllers often deteriorates when system parameters vary or external disturbances occur. To address this limitation, this study investigates a fuzzy self-tuning PID controller designed to improve both transient response and disturbance rejection in DC motor speed control. The research is conducted through mathematical modeling of a separately excited DC motor and the development of two controllers—a fixed-gain PID and a fuzzy self-tuning PID. The fuzzy controller adjusts the PID gains in real time based on the speed error and its derivative using a Mamdani inference system. MATLAB and Simulink are used as the main tools for system modeling, controller implementation, and simulation. Motor parameters are collected from standard DC motor specifications. Simulation results show that the fuzzy self-tuning PID controller achieves faster response, reduced overshoot, and significantly improved robustness to load disturbances compared with the conventional PID. These findings indicate that fuzzy self-tuning PID control is an effective and practical approach for enhancing DC motor performance in uncertain or varying operating conditions.