Optimization of PID Controller for Non-Minimum Phase System using Genetic Algorithm

Abstract

This paper describes the optimized PID controller design for a non-minimum phase system in order to have a wide comparison with conventional control techniques. Initially the system is controlled using PID controller and also a conventional technique known as Smith's predictor which is widely popular to control a system with time-delay. Though NMP system has zeroes in the right half of s-plane due to which it gives undershoots response. Here, conventional PID controller is designed using various tuning techniques like Ziegler-Nichols, Chien-Hrones & Reswick and IMC methods. These, criterions are unable to satisfy the time-domain specifications as desired. To accomplish all the design requirements, the NMP system is controlled using Smith's predictor. Smith's controller tries to incorporate the designed requirements better than the conventional controller but fails in achieving all the requirements. Therefore, a well-known meta-heuristic technique known as Genetic algorithm (GA) is implemented here to optimize the parameters of PID controller in order to compensate the system's performance. The parameter is optimized on the basis of minimizing the value of integral square error (ISE) of the system and provides better accuracy in terms of rise time, settling time and peak time.