DocumentCode :
989369
Title :
Robust model predictive control for LPV systems using relaxation matrices
Author :
Lee, S.M. ; Park, J.H. ; Ji, D.H. ; Won, S.C.
Author_Institution :
KT Co. Ltd., Daejeon
Volume :
1
Issue :
6
fYear :
2007
fDate :
11/1/2007 12:00:00 AM
Firstpage :
1567
Lastpage :
1573
Abstract :
A method of computing a new model predictive control (MPC) law for linear parameter varying systems with input constraints is proposed. The proposed method improves feasibility and system performance by deriving a new sufficient condition for the cost monotonicity. The control problem is formulated as a minimisation of the upper bound of finite horizon cost function satisfying the sufficient conditions. The relaxation matrices yield less conservative sufficient condition in terms of linear matrix inequalities so that it allows to design a more robust MPC. A numerical example is included to illustrate the effectiveness of the proposed method.
Keywords :
linear matrix inequalities; linear systems; predictive control; time-varying systems; linear matrix inequalities; linear parameter varying system; relaxation matrices; robust model predictive control;
fLanguage :
English
Journal_Title :
Control Theory & Applications, IET
Publisher :
iet
ISSN :
1751-8644
Type :
jour
DOI :
10.1049/iet-cta:20060525
Filename :
4389824
Link To Document :
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