Design of multivariable PID controller using DE-PSO

Abstract

This paper presents design of multivariable PID controller using a novel method differential evolution (DE)-based particle swarm optimisation (PSO) for two-input two-output (TITO) processes and its performance compare with evolutionary algorithms (EAs) like DE and modified PSO methods. In the proposed DE-PSO method, preliminary DE is applied on the random generated population then PSO is used to update the position and velocity of the particles. To validate the effectiveness of the proposed DE-PSO method, two different industrial processes and real time experiment on four tank level control system is considered. Simulation results show that DE-based PSO is better than both MPSO and DE in terms of getting global optimum in less iterations and avoiding premature convergence.