PID controller tuning parameters using meta-heuristics algorithms: Comparative analysis

Abstract

Proportional-Integral-Derivative (PID)Controller is a primary component in industrial control systems nowadays. Gain parameters of it have a powerful effect on transient response’s criteria such as integral squared error (ISE), settling time, rise time and overshooting. The power control systems that have the minimum of these criteria. Tuning the parameters to deliver the active case of the transient response of control systems is a hard problem. The traditional method is Ziegler-Nicolas (ZN) method that initially computes the values of the parameters. Meta-heuristics are used to tune these initial parameters’ values to produce more stable transient response has minimum criteria. In this chapter Particle Swarm Optimization algorithm, Genetic algorithm and Sine-Cosine Optimization algorithm are used to tune the parameters of PID controller by minimizing the ISE function and compared the result with that produced by Ziegler-Nicolas method.