Multiobjective Tuning of Robust GPC Controllers using Evolutionary Algorithms

Abstract

[EN] In this article a procedure to tune robust Generalized Predictive Controllers (GPC) is presented. To tune the controller parameters a multiobjective optimization problem is formulated so the designer can consider conflicting objectives simultaneously without establishing any prior preference. Moreover model uncertainty, represented by a list of possible models, is considered. The multiobjective problem is solved with a specifc Evolutionary Algorithm (ev-MOGA). Finally, an application to a non-linear thermal process is presented to illustrate the technique.