DocumentCode
2574879
Title
Performance-lossless complexity reduction in Explicit MPC
Author
Kvasnica, Michal ; Fikar, Miroslav
Author_Institution
Inst. of Inf. Eng., Autom., & Math., Slovak Univ. of Technol. in Bratislava, Bratislava, Slovakia
fYear
2010
fDate
15-17 Dec. 2010
Firstpage
5270
Lastpage
5275
Abstract
The idea of Explicit Model Predictive Control (MPC) is to find the optimal control input as an explicit Piecewise Affine (PWA) function of the initial conditions. The function, however, is often too complex to be processed by a typical control hardware setup in real time. Therefore the paper proposes a novel method of replacing a generic continuous PWA function by a different function of significantly lower complexity in such a way that optimal closed-loop performance, stability and constraint satisfaction are preserved. The idea is based on eliminating a significant portion of the regions of the PWA function over which the function attains a saturated value. An extensive case study is presented which confirms that a significant reduction of complexity is achieved in general.
Keywords
closed loop systems; optimal control; predictive control; stability; constraint satisfaction; explicit model predictive control; explicit piecewise affine function; optimal closed-loop performance; optimal control input; performance-lossless complexity reduction; stability; Complexity theory; Hardware; Indexes; Joints; Memory management; Merging; Optimal control;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location
Atlanta, GA
ISSN
0743-1546
Print_ISBN
978-1-4244-7745-6
Type
conf
DOI
10.1109/CDC.2010.5717578
Filename
5717578
Link To Document