DocumentCode :
2240623
Title :
MPC for uncertain systems using the Youla parameterizations
Author :
Thomsen, Sven Creutz ; Niemann, Henrik ; Poulsen, Niels Kjølstad
Author_Institution :
Dept. of Inf. & Math. Modeling, Tech. Univ. of Denmark, Lyngby, Denmark
fYear :
2008
fDate :
9-11 Dec. 2008
Firstpage :
3421
Lastpage :
3426
Abstract :
Several approaches have been taken in the past to deal with uncertainty in constrained predictive control. The major drawbacks of these efforts are usually either conservativeness and/or on-line computational complexity. In this work we examine the possibility of dealing with uncertainty through the use of the primary and the dual Youla parameterizations. The dual Youla parameter can be seen as a frequency weighted measure of the uncertainty and the primary Youla parameter can be seen as a controller for this uncertainty. The work is an application of the methodology to constraint control.
Keywords :
computational complexity; predictive control; uncertain systems; MPC; computational complexity; constrained predictive control; constraint control; dual Youla parameter; model predictive control; uncertain systems; Computational complexity; Control systems; Cost function; Frequency measurement; Industrial control; Measurement uncertainty; Predictive control; Predictive models; Uncertain systems; Weight measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2008. CDC 2008. 47th IEEE Conference on
Conference_Location :
Cancun
ISSN :
0191-2216
Print_ISBN :
978-1-4244-3123-6
Electronic_ISBN :
0191-2216
Type :
conf
DOI :
10.1109/CDC.2008.4738799
Filename :
4738799
Link To Document :
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