Model-Based Predictive Control Using Differential Evolution Applied to a Pressure System

Abstract

Model-Based Predictive Control techniques have been applied industrially since the 1970s, presenting favorable characteristics. Among them, it can be mentioned the treatment of process constraints and optimization considering the output error with respect to the reference and the used energy. Usually, formulations based on linear models of the plant are used. However, the use of linear models for nonlinear plants can result in control loops with limited or even reduced performance. In this paper, the use of a Model-Based Predictive Control approach using a Differential Evolution algorithm for optimization applied in a pressure control system is presented. The results show the advantages found by using such nonlinear formulation. The methodology used, with comments about the obtained results and conclusions on this line of research are presented.