DocumentCode :
1102496
Title :
Robust Kalman filtering for uncertain discrete-time systems
Author :
Xie, Lihua ; Soh, Yeng Chai ; de Souza, Carlos E.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume :
39
Issue :
6
fYear :
1994
fDate :
6/1/1994 12:00:00 AM
Firstpage :
1310
Lastpage :
1314
Abstract :
This paper is concerned with the problem of a Kalman filter design for uncertain discrete-time systems. The system under consideration is subjected to time-varying norm-bounded parameter uncertainty in both the state and output matrices. The problem addressed is the design of a linear filter such that the variance of the filtering error is guaranteed to be within a certain bound for all admissible uncertainties. Furthermore, the guaranteed cost can be optimized by appropriately searching a scaling design parameter
Keywords :
Kalman filters; discrete time systems; filtering and prediction theory; matrix algebra; optimisation; Kalman filter; design cost optimisation; filtering error; output matrix; scaling design parameter; state matrix; time varying norm bounded parameter uncertainty; uncertain discrete time systems; Adaptive control; Automatic control; Control systems; Filtering; Kalman filters; Neural networks; Nonlinear filters; Notice of Violation; Programmable control; Robustness;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/9.293203
Filename :
293203
Link To Document :
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