A Comparative Study of Particle Swarm Optimization based Optimizations

Proportional-Integral-Derivative (PID) control is the most commonly used algorithm for industrial control. of computing and setting the optimal gains for P, I and D to get an ideal response from a control system, called as tuning, is a very difficult task. In this paper, two types of nature inspired algorithms genetic algorithm (GA) and particle swarm optimization (PSO) techniques are used for optimizing the PID parameters. These techniques have been observed to be capable of locating high performance areas in complex domains without experiencing the difficulties associated with high d or false optima. Hard disk drive read/write head servo control system and DC motor control are used in the depicting the efficacy of the proposed methods. optimized using GA and PSO are observed to domain performance in comparison with conventionally tuning method of Ziegler-Nichols.