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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/6037

Title: Probability-dependent gain-scheduled filtering for stochastic systems with missing measurements
Authors: Wei, G
Wang, Z
Shen, B
Li, M
Keywords: Filtering
Gain scheduling
Missing measurements
Probability-dependent Lyapunov functions
Time-varying Bernoulli distribution
Publication Date: 2011
Publisher: IEEE
Citation: IEEE Transactions on Circuits and Systems II: Express Briefs, 58(11): 753 - 757, Nov 2011
Abstract: This brief addresses the gain-scheduled filtering problem for a class of discrete-time systems with missing measurements, nonlinear disturbances, and external stochastic noise. The missing-measurement phenomenon is assumed to occur in a random way, and the missing probability is time-varying with securable upper and lower bounds that can be measured in real time. The multiplicative noise is a state-dependent scalar Gaussian white-noise sequence with known variance. The addressed gain-scheduled filtering problem is concerned with the design of a filter such that, for the admissible random missing measurements, nonlinear parameters, and external noise disturbances, the error dynamics is exponentially mean-square stable. The desired filter is equipped with time-varying gains based primarily on the time-varying missing probability and is therefore less conservative than the traditional filter with fixed gains. It is shown that the filter parameters can be derived in terms of the measurable probability via the semidefinite program method.
Description: Copyright @ 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Sponsorship: This work was supported in part by the Leverhulme Trust of the U.K., the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the National Natural Science Foundation of China under Grants 61028008, 61074016 and 60974030, the Shanghai Natural Science Foundation of China under Grant 10ZR1421200, and the Alexander von Humboldt Foundation of Germany.
URI: http://bura.brunel.ac.uk/handle/2438/6037
DOI: http://dx.doi.org/10.1109/TCSII.2011.2168018
ISSN: 1549-7747
Appears in Collections:School of Information Systems, Computing and Mathematics Research Papers
Electronic and Computer Engineering
Publications
Computer Science

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