DocumentCode
2276929
Title
Feedback min-max model predictive control based on a quadratic cost function
Author
De la Pena, D. Munoz ; Alamo, T. ; Bemporad, A. ; Camacho, E.F.
Author_Institution
Dept. de Ingenieria de Sistemas y Automatica, Univ. de Sevilla
fYear
2006
fDate
14-16 June 2006
Abstract
Feedback min-max model predictive control based on a quadratic cost function is addressed in this paper. The main contribution is an algorithm for solving the min-max quadratic MPC problem with an arbitrary degree of approximation. The paper also introduces the "recourse horizon", which allows one to obtain a trade-off between computational complexity and performance of the control law. The results are illustrated by means of a simulation of a quadruple-tank process
Keywords
feedback; linear systems; minimax techniques; predictive control; robust control; computational complexity; feedback min-max model predictive control; linear systems; optimization algorithms; quadratic cost function; quadruple-tank process; recourse horizon; robust control; Approximation algorithms; Cost function; Feedback; Linear systems; Mathematical model; Predictive control; Predictive models; Robust control; Uncertainty; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2006
Conference_Location
Minneapolis, MN
Print_ISBN
1-4244-0209-3
Electronic_ISBN
1-4244-0209-3
Type
conf
DOI
10.1109/ACC.2006.1656443
Filename
1656443
Link To Document