DocumentCode
404583
Title
Robust output-feedback integral MPC: a probabilistic approach
Author
Kanev, Stoyan ; Verhaegen, Michel
Author_Institution
Delft Center for Syst. & Control, Delft Univ. of Technol., Netherlands
Volume
2
fYear
2003
fDate
9-12 Dec. 2003
Firstpage
1914
Abstract
In this paper a new approach for robust output-feedback control is presented. The approach consists of a combination of a Kalman filter and a finite-horizon MPC into one min-max (worst-case) optimization problem. The class of uncertainties considered is quite general as it is only assumed that the system matrices remain bounded over all uncertainties. In order to solve the underlying optimization problem an iterative approach is developed in a probabilistic framework.
Keywords
Kalman filters; convergence; feedback; iterative methods; matrix algebra; minimax techniques; predictive control; robust control; uncertain systems; Kalman filter; convergence; iterative approach; min-max optimization problem; robust output feedback integral model predictive control; state space matrices; Constraint optimization; Control systems; Ellipsoids; Kalman filters; Peak to average power ratio; Predictive models; Robust control; Robustness; Symmetric matrices; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
ISSN
0191-2216
Print_ISBN
0-7803-7924-1
Type
conf
DOI
10.1109/CDC.2003.1272895
Filename
1272895
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