Please use this identifier to cite or link to this item: https://doi.org/10.1109/TSP.2003.810303
Title: Reliable guaranteed variance filtering against sensor failures
Authors: Liu, J.
Wang, J.L.
Yang, G.-H. 
Keywords: Error variance minimization
LMI
Reliable filtering
Robust filter design
Sensor failure
Issue Date: May-2003
Citation: Liu, J., Wang, J.L., Yang, G.-H. (2003-05). Reliable guaranteed variance filtering against sensor failures. IEEE Transactions on Signal Processing 51 (5) : 1403-1411. ScholarBank@NUS Repository. https://doi.org/10.1109/TSP.2003.810303
Abstract: This paper presents a solution to a reliable filtering problem with error variance specifications for both continuous- and discrete-time systems. The filtering error variance in the sensor failure cases is guaranteed to be less than a given upper bound while the performance in the nominal case is optimized. A convergent iterative algorithm based on linear matrix inequality (LMI) is given to obtain the solution. The algorithm solves the problem without introducing additional conservativeness, and it is shown to get better performance and be less conservative compared with traditional LMI approaches. A numerical example is given to show the advantages of our approach over existing techniques.
Source Title: IEEE Transactions on Signal Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/111474
ISSN: 1053587X
DOI: 10.1109/TSP.2003.810303
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