Predictive controller tuning using modified particle swarm optimization based on Cauchy and Gaussian distributions

Model based predictive control has become an important form of advanced control. Generalised predictive controllers (GPO) have been successfully applied to control complex processes in the industry during the last decade. In this paper, we present a novel method named modified particle swarm optimization, which is based on Gaussian and Cauchy distributions for the optimization of an adaptive GPC using an ARMA (Auto Regressive Moving Average) mathematical model. The simulation results demonstrated the successful GPC tuning and the suitability of the modified particle swarm optimization for the control of a non-linear process of Hammerstein type.