Title :
Robustification of model predictive control
Author :
Quevedo, Daniel E. ; Salgado, Mario E.
Author_Institution :
Dept. of Electron. Eng., Univ. Tecnica Federico Santa Maria, Valparaiso, Chile
Abstract :
A general procedure leading to an enhancement of robustness of existing model predictive control techniques is proposed. This procedure, which considers additive modeling errors, is illustrated for the case of cautious stable predictive control. The basic idea is the augmentation of the cost function with an additional term related to a description of the nominal model uncertainty, leading either to a minimization or to a min-max optimization problem, depending on the class of error description being used
Keywords :
discrete time systems; minimax techniques; minimisation; predictive control; robust control; additive modeling errors; cautious stable predictive control; error description; min-max optimization problem; model predictive control; nominal model uncertainty; robustification; Cost function; Error correction; Open loop systems; Predictive control; Predictive models; Robust control; Robustness; Stability; Transfer functions; Uncertainty;
Conference_Titel :
Decision and Control, 2000. Proceedings of the 39th IEEE Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6638-7
DOI :
10.1109/CDC.2000.912753
