Min-Max MPC using a tractable QP Problem

Author

Alamo, T. ; Ramirez, D.R. ; De La pen, D. Munoz

Author_Institution

Depto. de Ing. de Sistemas y Automática, Universidad de Sevilla, Camino de los Descubrimientos s/n 41092 Sevilla, SPAIN, Phone: +34 954487346 Fax: +34954487340, email: alamo@cartuja.us.es.

fYear

2005

fDate

12-15 Dec. 2005

Firstpage

6210

Lastpage

6215

Abstract

Min-Max MPC (MMMPC) controllers [5] suffer from a great computational burden that is often circumvented by using upper bounds of the worst possible case of a performance index. These upper bounds are usually computed by means of linear matrix inequalities (LMI) techniques. In this paper a more efficient approach is shown. This paper proposes a computationally efficient MMMPC control strategy in which a close approximation of the solution of the min-max problem is computed using a quadratic programming problem. The overall computational burden is much lower than that of the min-max problem and the resulting control is shown to have guaranteed stability. Simulation examples are given in the paper.

Keywords

Min-max; Model predictive control; Robust control; Uncertain systems; Computational modeling; Contracts; Linear matrix inequalities; Performance analysis; Predictive control; Predictive models; Quadratic programming; Stability; Uncertainty; Upper bound; Min-max; Model predictive control; Robust control; Uncertain systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC '05. 44th IEEE Conference on

Print_ISBN

0-7803-9567-0

Type

conf

DOI

10.1109/CDC.2005.1583156

Filename

1583156