Comparative Performance Study of Evolutionary and Immune Algorithm based PID Controller Tuning for Speed Control of DC Motor Drives

Abstract

Biological immune system (BIS) and Biological Evolutionary system (BES) is a special type of control system that has shown strong robustness and selfadaptability. In this thesis report artificial immune system algorithm and biological evolutionary system used to develop are immune controller and evolutionary controller. The idea of immune controller and evolutionary controller is adopted and derived from biological vertebrate immune and evolutionary system, mimicking and imitating of biological immune and evolutionary system which is better known as the artificial immune and evolutionary system. Immune and Evolutionary are stochastic optimization techniques based on the principle of natural evolution. We describe the general functioning of EAs and BIS. The aim of this subject is to design a speed controller for a DC motor by selection of PID parameters using “Evolutionary and Immune.” These algorithms come under the category of bio-inspired optimization techniques. The model of a DC motor is considered as a second order system for speed control. Here, there is a comparison between conventional tuning methods and optimization techniques of parameters for PID controller. In some cases, it was found that the proposed PID parameters adjusted by optimization technique is better than the conventional techniques like a Ziegler-Nichols’ method. These proposed optimization methods could be applied for higher order system also to provide better system performance with minimum errors. It is decided to create an objective function which will evaluate the optimum PID gains based on the controlled systems and overall error. In this thesis we have taken into account the various configurations of PID controllers in Evolutionary and Immune algorithm to measure the performance of the controller for the dc motor drive system.