DocumentCode :
2844334
Title :
Alternative parameterisations for predictive control: How and why?
Author :
Valencia-Palomo, G. ; Rossiter, J.A. ; Jones, C.N. ; Gondhalekar, R. ; Khan, Bilal
Author_Institution :
Inst. Tecnol. de Hermosillo, Hermosillo, Mexico
fYear :
2011
fDate :
June 29 2011-July 1 2011
Firstpage :
5175
Lastpage :
5180
Abstract :
This paper looks at the efficiency of the parameterisation of the degrees of freedom within an optimal predictive control algorithm. It is shown that the conventional approach of directly determining each individual future control move is not efficient in general, and can give poor feasibility when the number of degrees of freedom are limited. Two systematic alternatives are explored and both shown to be far more efficient in general.
Keywords :
optimal control; predictive control; stochastic processes; Laguerre functions; optimal predictive control algorithm; parameterisation; Matrix decomposition; Optimization; Polynomials; Prediction algorithms; Predictive models; Stability analysis; Systematics; Laguerre functions; MPC; feasibility volumes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2011
Conference_Location :
San Francisco, CA
ISSN :
0743-1619
Print_ISBN :
978-1-4577-0080-4
Type :
conf
DOI :
10.1109/ACC.2011.5990639
Filename :
5990639
Link To Document :
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