Modern Optimization Techniques Based PID Controller Tuning for the Speed Control of a DC Motor

Abstract

In this paper, the optimal configuration of the Proportional Integral Derivative (PID) controller for the speed control of a DC motor are determined and compared using five optimization algorithms. The five optimization algorithms are respectively Ant Lion Optimization (ALO), Grey Wolf Optimizer (GWO), Moth-Flame Optimization (MFO), Multi-Verse Optimization (MVO) and Salp Swarm Optimization (SSO). The objective function uses The Integral of Time multiplied by Absolute Error (ITAE) as the performance index. A comparison of all these methods is done using the following step response parameters - steady-state error, settling time, maximum overshoot and rise time. ALO performed best among all the optimization algorithms.