Elaboration de méthodes de robustification de lois de commande prédictive

Abstract

This work (describes a methology ) we use the dual Youla parameterisation approach for the robustification of predictive linear control system s using LMI-based constraints. This method based on an approach of convex optimization, is use d to robustify the generalized predictive controller GPC algorithm applied to an AutoRegressi ve Integrated Moving Average (CARIMA) model. The design method consists of two s teps. In the first step the synthesis and the robustification of the initial polynomial c ontroller RST-GPC is carried out. This is achieved under constraints on the system output, th e control signal and its increment represented as LMI using Youla parameterisation. Th is controller is then robustified considering frequency and time-domain constraints. In the second step, the new controller is robustified by a dual Youla parameterisation consid ering frequential and temporal constraints. The effectiveness of this methodology are demonstrated and applied for position control of an induction motor drive.