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 :
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