DocumentCode :
50164
Title :
MPC for Sampled-Data Linear Systems: Guaranteeing Constraint Satisfaction in Continuous-Time
Author :
Sopasakis, Pantelis ; Patrinos, Panagiotis ; Sarimveis, Haralambos
Author_Institution :
IMT Inst. for Adv. Studies Lucca, Lucca, Italy
Volume :
59
Issue :
4
fYear :
2014
fDate :
Apr-14
Firstpage :
1088
Lastpage :
1093
Abstract :
Model Predictive Controllers (MPC) designed for sampled-data systems can be shown to violate the constraints in continuous time. A reformulation of the initial problem will guarantee constraint satisfaction throughout the intersample period. Polytopic inclusions of the continuous trajectory are used in this technical note to establish additional constraints leading to a linearly constrained quadratic optimization problem. Continuous time asymptotic stability and continuous-time positive invariance are proven for the reformulated problem.
Keywords :
approximation theory; asymptotic stability; constraint satisfaction problems; continuous time systems; control system synthesis; linear programming; linear systems; predictive control; quadratic programming; sampled data systems; MPC; constraint satisfaction; continuous time asymptotic stability; continuous trajectory; continuous-time positive invariance; intersample period; linearly constrained quadratic optimization problem; model predictive controllers; polytopic inclusions; polytopic overapproximation; reformulated problem; sampled-data linear systems; Asymptotic stability; Closed loop systems; Convergence; Optimization; Prediction algorithms; Predictive control; Trajectory; Continuous invariance; model predictive control; polytopic overapproximation; sampled data;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.2013.2285786
Filename :
6632877
Link To Document :
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