H sub( infinity ) filtering for discrete-time systems subject to stochastic missing measurements: a decomposition approach

This paper deals with the problem of H sub( infinity ) filtering for discrete-time systems with stochastic missing measurements. A new missing measurement model is developed by decomposing the interval of the missing rate into several segments. The probability of the missing rate in each subsegment...

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Bibliographic Details
Published inInternational journal of systems science Vol. 45; no. 7; pp. 1356 - 1363
Main Authors Gu, Zhou, Fei, Shumin, Yue, Dong, Tian, Engang
Format Journal Article
LanguageEnglish
Published 01.01.2014
Subjects
Constraints
Decomposition
Design engineering
Filtering
Filtration
Intervals
Rejection
Stochasticity
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ISSN0020-7721
1464-5319
DOI10.1080/00207721.2013.871372

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Summary:This paper deals with the problem of H sub( infinity ) filtering for discrete-time systems with stochastic missing measurements. A new missing measurement model is developed by decomposing the interval of the missing rate into several segments. The probability of the missing rate in each subsegment is governed by its corresponding random variables. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square with a less conservatism while the disturbance rejection attenuation is constrained to a given level by means of an H sub( infinity ) performance index. Based on Lyapunov theory, the reliable filter parameters are characterised in terms of the feasibility of a set of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.
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ISSN:0020-7721
1464-5319
DOI:10.1080/00207721.2013.871372