Title :
A Decomposition Algorithm for Feedback Min-Max Model Predictive Control
Author :
De la Pena, D. Munoz ; Alamo, T. ; Bemporad, A.
Author_Institution :
Dep. de Ingeniería de Sistemas y Automática, Universidad de Sevilla, Spain. E-mail: davidmps@cartuja.us.es
Abstract :
An algorithm for solving feedback min-max model predictive control for discrete time uncertain linear systems with constraints is presented in the paper. The algorithm solves the corresponding multi-stage min-max linear optimization problem. It is based on applying recursively a decomposition technique to solve the min-max problem via a sequence of low complexity linear programs. It is proved that the algorithm converges to the optimal solution in finite time. Simulation results are provided to compare the proposed algorithm with other approaches.
Keywords :
Optimization algorithms; Predictive control for linear systems; Uncertain systems; Cost function; Dynamic programming; Feedback; Linear systems; Open loop systems; Predictive control; Predictive models; Robust control; Uncertainty; Vectors; Optimization algorithms; Predictive control for linear systems; Uncertain systems;
Conference_Titel :
Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC '05. 44th IEEE Conference on
Print_ISBN :
0-7803-9567-0
DOI :
10.1109/CDC.2005.1582975