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dc.contributor.authorYang, Fuwenen_US
dc.contributor.authorHan, Qing-Longen_US
dc.contributor.authorLiu, Yurongen_US
dc.description.abstractThis paper is concerned with the distributed H∞ state estimation for a discrete-time target linear system over a filtering network with time-varying and switching topology and partial information exchange. Both filtering network topology switching and partial information exchange between filters are simultaneously considered in the filter design. The topology under consideration evolves not only over time but also by an event switch which is assumed to be subject to a nonhomogeneous Markov chain. The probability transition matrix of the nonhomogeneous Markov chain is time-varying. In the filter information exchange, partial state estimation information and channel noise are simultaneously considered. In order to design such a switching filtering network with partial information exchange, stochastic Markov stability theory is developed. The switching topology-dependent filters are derived to guarantee an optimal H∞ disturbance rejection attenuation level for the estimation disagreement of the filtering network. It is shown that the addressed H∞ state estimation problem is turned into a switching topology-dependent optimal problem. The distributed filtering problem with complete information exchanges from its neighbors is also investigated. An illustrative example is given to show the applicability of the obtained results.en_US
dc.publisher.placeUnited Statesen_US
dc.relation.ispartofjournalIEEE Transactions on Cyberneticsen_US
dc.subject.fieldofresearchElectrical and Electronic Engineering not elsewhere classifieden_US
dc.titleDistributed H∞ State Estimation Over a Filtering Network With Time-Varying and Switching Topology and Partial Information Exchangeen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dc.type.codeC - Journal Articlesen_US
gro.facultyGriffith Sciences, School of Engineering and Built Environmenten_US
gro.description.notepublicThis publication has been entered into Griffith Research Online as an Advanced Online Version.en_US
gro.hasfulltextNo Full Text

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