DocumentCode
2086660
Title
Characterization of min-max MPC with bounded uncertainties and a quadratic criterion
Author
Ramírez, D.R. ; Camacho, E.F.
Author_Institution
Departamento de Ingenieria de Sistemas y Automatica, Seville Univ., Spain
Volume
1
fYear
2002
fDate
2002
Firstpage
358
Abstract
As shown by the authors in their previous paper (2001), min-max model predictive control (MPC) with a quadratic criterion, bounded additive uncertainties and a linear prediction model, results in a piecewise linear controller, which can be described in explicit form. This paper presents a characterization of these controllers. Techniques for composing a list of candidates for the optimal solution and for testing their optimality are presented. The results are illustrated by means of examples.
Keywords
control system analysis; minimax techniques; predictive control; bounded uncertainty; cost function; minimax method; model predictive control; objective function; optimality; quadratic criterion; Equations; Mathematical model; Optimal control; Piecewise linear techniques; Predictive models; Quadratic programming; Robust control; Robust stability; Testing; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2002. Proceedings of the 2002
ISSN
0743-1619
Print_ISBN
0-7803-7298-0
Type
conf
DOI
10.1109/ACC.2002.1024830
Filename
1024830
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