Optimal tuning of PID controller using GWO algorithm for speed control in DC motor

摘要

This paper introduces a bio-inspired meta-heuristic soft computing method to optimize the performance of a PID controller used in DC motor speed control. APID controller is designed for an adopted second order DC motor system and the evolutionary algorithm based on Grey Wolf Optimizer is used to optimize the controller. In MATLAB/Simulink environment, the best set of PID parameters thus obtained from the optimization are used with a step input to the DC motor to get the transient response specifications such as rise time, settling time, maximum over shoot and steady state error. These results are then compared with results from other conventional techniques and soft computing methods to look for the most efficient method to get best transient response in a DC Motor.