Grey wolf, gravitational search and particle swarm optimizers: A comparison for PID controller design

Abstract

Nature and biologically inspired metaheuristics can be powerful tools to design PID controllers. The grey wolf optimization is one of these promising and interesting metaheuristics, recently introduced. In this study the grey wolf optimization algorithm is proposed to design PID controllers, and the results obtained compared with the ones obtained with gravitational search and particle swarm optimization algorithms. Simulation results obtained with these three bio-inspired metaheuristics applied to a set of benchmark linear plants are presented, considering the design objective of set-point tracking. The results are also compared with two non-iterative PID tuning techniques.