Separating Functions for Complexity Reduction of Explicit Model Predictive Control
I. Rauová, M. Kvasnica, M. Fikar
Slovak University of Technology in Bratislava
Abstract
In this work we propose to reduce memory footprint of explicit MPC controllers by eliminating a significant portion of controller's regions in which the value of the optimal control action attains saturated values. Such regions are then separated by a suitable function, which serves to recover the original control behavior. As a consequence, complexity of explicit MPC feedback laws is reduced considerably without sacrificing optimality.
Full paper
Session
Model Predictive Control (Lecture)
Reference
Rauová, I.; Kvasnica, M.; Fikar, M.: Separating Functions for Complexity Reduction of Explicit Model Predictive Control. Editors: Fikar, M. and Kvasnica, M., In Proceedings of the 18th International Conference on Process Control, Tatranská Lomnica, Slovakia, June 14 – 17, 427–433, 2011.
BibTeX
| @inProceedings{pc2011-035, | ||
| author | = { | Rauov\'a, I. and Kvasnica, M. and Fikar, M.}, |
| title | = { | Separating Functions for Complexity Reduction of Explicit Model Predictive Control}, |
| booktitle | = { | Proceedings of the 18th International Conference on Process Control}, |
| year | = { | 2011}, |
| pages | = { | 427-433}, |
| editor | = { | Fikar, M. and Kvasnica, M.}, |
| address | = { | Tatransk\'a Lomnica, Slovakia}, |
| publisher | = { | Slovak University of Technology in Bratislava}, |
| url | = { | http://www.kirp.chtf.stuba.sk/pc11/data/papers/035.pdf}} |