Advanced Speed Control of DC Motors by Tuning Classical PID Controllers, using Fuzzy Logic Technique

Abstract

This study introduces a PID controller tuning approach that combines the Ziegler–Nichols method with fuzzy logic, aimed at regulating the speed of a DC motor. In this approach, the proportional, integral, and derivative gains (Kp, Ki, Kd) of the PID controller are adjusted based on fuzzy logic principles. The fuzzy logic-based PID (FLPID) controller is designed using a set of 25 self-tuning rules, which dynamically adjust the PID parameters. The controller takes two inputs: the speed error (difference between actual and desired speed) and the rate of change of the speed error. These inputs are used to regulate the PID parameters to achieve optimal speed control of the DC motor. The MATLAB model of the speed control system using fuzzy logic requires minimal calculations, making it efficient and straightforward to implement. Simulation results show that the self-tuned FLPID controller achieves superior speed control compared to the conventional PID controller, validating the effectiveness of this design.