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Robust filtering for uncertain discrete-time systems with uncertain noise covariance and uncertain observations

Mohamed, Shady M. Korany and Nahavandi, Saeid 2008, Robust filtering for uncertain discrete-time systems with uncertain noise covariance and uncertain observations, in INDIN 2008 : Proceedings of the 6th IEEE International Conference on Industrial Informatics, IEEE, Piscataway, N.J., pp. 667-672, doi: 10.1109/INDIN.2008.4618185.

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Title Robust filtering for uncertain discrete-time systems with uncertain noise covariance and uncertain observations
Author(s) Mohamed, Shady M. KoranyORCID iD for Mohamed, Shady M. Korany orcid.org/0000-0002-8851-1635
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Conference name IEEE International Conference on Industrial Informatics (6th : 2008 : Daejeon, Korea)
Conference location Daejeon, Korea
Conference dates 13-16 July 2008
Title of proceedings INDIN 2008 : Proceedings of the 6th IEEE International Conference on Industrial Informatics
Editor(s) [Unknown]
Publication date 2008
Conference series International Conference on Industrial Informatics
Start page 667
End page 672
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Summary The use of Kalman filtering is very common in state estimation problems. The problem with Kalman filters is that they require full prior knowledge about the system modeling. It is also assumed that all the observations are fully received. In real applications, the previous assumptions are not true all the time. It is hard to obtain the exact system model and the observations may be lost due to communication problems. In this paper, we consider the design of a robust Kalman filter for systems subject to uncertainties in the state and white noise covariances. The systems under consideration suffer from random interruptions in the measurements process. An upper bound for the estimation error covariance is proposed. The proposed upper bound is further minimized by selection of optimal filter parameters. Simulation example shows the effectiveness of the proposed filter.
Notes ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 9781424421718
Language eng
DOI 10.1109/INDIN.2008.4618185
Field of Research 080610 Information Systems Organisation
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2008, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30018330

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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