Tuning of parameters of PID controller using Grey Wolf Optimizer

Abstract

In this paper, the Grey Wolf Optimizer (GWO) is used for tuning the parameters of PID (Proportional, Integral and Derivative) controller. The GWO is a meta-heuristic approach inspired by grey wolves (Canis lupus). The GWO algorithm consists of four types of grey wolves known as alpha (∝) as a leader or decision maker, beta (𝛽) as to assist alpha in decision making, delta (𝛿) as a subordinate wolf and omegas (𝜔) the followers. The hunting behavior of GWO continues with the three main following steps and they are searching for prey, encircling the prey and attacking the prey. Firstly, the parameters of the PID controller are tuned using the Ziegler-Nichols (Z-N) technique. Then these tuned parameters along with some randomly assumed coefficients are used as the first iteration step for the GWO algorithm. The tuning principle of GWO ensures the minimization of performance index. The performance index used in this paper is Integral Square error (ISE). The GWO algorithm for tuning the parameters of PID controller is validated by controlling the highly nonlinear in-verted pendulum system. Simulation results showed that the GWO algorithm minimizes the ISE of the system and stabilized the system within the stipulated time.