Distributed state estimation for uncertain Markov-type sensor networks with mode-dependent distributed delays

SUMMARY In this paper, the distributed state estimation problem is investigated for a class of sensor networks described by uncertain discrete‐time dynamical systems with Markovian jumping parameters and distributed time‐delays. The sensor network consists of sensor nodes characterized by a directed...

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Published inInternational journal of robust and nonlinear control Vol. 22; no. 3; pp. 331 - 346
Main Authors Liang, Jinling, Wang, Zidong, Liu, Xiaohui
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 01.02.2012
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ISSN1049-8923
1099-1239
DOI10.1002/rnc.1699

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Summary:SUMMARY In this paper, the distributed state estimation problem is investigated for a class of sensor networks described by uncertain discrete‐time dynamical systems with Markovian jumping parameters and distributed time‐delays. The sensor network consists of sensor nodes characterized by a directed graph with a nonnegative adjacency matrix that specifies the interconnection topology (or the distribution in the space) of the network. Both the parameters of the target plant and the sensor measurements are subject to the switches from one mode to another at different times according to a Markov chain. The parameter uncertainties are norm‐bounded that enter into both the plant system as well as the network outputs. Furthermore, the distributed time‐delays are considered, which are also dependent on the Markovian jumping mode. Through the measurements from a small fraction of the sensors, this paper aims to design state estimators that allow the nodes of the sensor network to track the states of the plant in a distributed way. It is verified that such state estimators do exist if a set of matrix inequalities is solvable. A numerical example is provided to demonstrate the effectiveness of the designed distributed state estimators. Copyright © 2011 John Wiley & Sons, Ltd.
Bibliography:istex:29A3A6A0672CB3DC472B80A443805627F5EF53D3
ark:/67375/WNG-V5TQXNZK-0
ArticleID:RNC1699
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.1699