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Article: Distributed H∞ filtering for repeated scalar nonlinear systems with random packet losses in sensor networks

TitleDistributed H∞ filtering for repeated scalar nonlinear systems with random packet losses in sensor networks
Authors
KeywordsDiscrete-time
Distributed filtering
Filtering problems
H indices
Measurement information
Issue Date2011
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207721.asp
Citation
International Journal of Systems Science, 2011, v. 42 n. 9, p. 1507-1519 How to Cite?
AbstractThis article is concerned with the distributed H∞ filtering problem for sensor networks with repeated scalar nonlinearities and multiple probabilistic packet losses. The class of nonlinear systems is represented by a discrete-time state-space model involving repeated scalar nonlinearities that cover several types of frequently investigated nonlinearities as special cases. A number of stochastic variables, all of which are mutually independent but satisfy a certain probabilistic distribution in the interval [0, 1], are introduced to account for the packet dropout phenomena occurring in the channels from the original system to the networked sensors. The concept of average H index is first introduced to measure the overall performance of the sensor networks. Then, by utilising available measurement information from not only each individual sensor but also its neighbouring sensors according a given topology, stability analysis is carried out to obtain sufficient conditions for ensuring stochastic stability as well as the prescribed average H∞ performance constraint. The solution of the parameters of the distributed filters is characterised in terms of the feasibility of a convex optimisation problem. Finally, a simulation study is conducted for a factory production line in order to demonstrate the effectiveness of the developed theoretical results. © 2011 Taylor & Francis.
Persistent Identifierhttp://hdl.handle.net/10722/157132
ISSN
2015 Impact Factor: 1.947
2015 SCImago Journal Rankings: 1.083
ISI Accession Number ID
Funding AgencyGrant Number
University of Hong KongHKU/CRCG/200907176129
National Natural Science Foundation of China60834003
61004067
Foundation for the Author of National Excellent Doctoral Dissertation of China2007B4
Funding Information:

This work was supported in part by the University of Hong Kong under Grant No. HKU/CRCG/200907176129, the National Natural Science Foundation of China under Grant No. 60834003 and 61004067 and the Foundation for the Author of National Excellent Doctoral Dissertation of China under Grant No. 2007B4.

References

 

DC FieldValueLanguage
dc.contributor.authorDong, Hen_US
dc.contributor.authorLam, Jen_US
dc.contributor.authorGao, Hen_US
dc.date.accessioned2012-08-08T08:45:28Z-
dc.date.available2012-08-08T08:45:28Z-
dc.date.issued2011en_US
dc.identifier.citationInternational Journal of Systems Science, 2011, v. 42 n. 9, p. 1507-1519en_US
dc.identifier.issn0020-7721en_US
dc.identifier.urihttp://hdl.handle.net/10722/157132-
dc.description.abstractThis article is concerned with the distributed H∞ filtering problem for sensor networks with repeated scalar nonlinearities and multiple probabilistic packet losses. The class of nonlinear systems is represented by a discrete-time state-space model involving repeated scalar nonlinearities that cover several types of frequently investigated nonlinearities as special cases. A number of stochastic variables, all of which are mutually independent but satisfy a certain probabilistic distribution in the interval [0, 1], are introduced to account for the packet dropout phenomena occurring in the channels from the original system to the networked sensors. The concept of average H index is first introduced to measure the overall performance of the sensor networks. Then, by utilising available measurement information from not only each individual sensor but also its neighbouring sensors according a given topology, stability analysis is carried out to obtain sufficient conditions for ensuring stochastic stability as well as the prescribed average H∞ performance constraint. The solution of the parameters of the distributed filters is characterised in terms of the feasibility of a convex optimisation problem. Finally, a simulation study is conducted for a factory production line in order to demonstrate the effectiveness of the developed theoretical results. © 2011 Taylor & Francis.en_US
dc.languageengen_US
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207721.aspen_US
dc.relation.ispartofInternational Journal of Systems Scienceen_US
dc.subjectDiscrete-timeen_US
dc.subjectDistributed filteringen_US
dc.subjectFiltering problemsen_US
dc.subjectH indicesen_US
dc.subjectMeasurement informationen_US
dc.titleDistributed H∞ filtering for repeated scalar nonlinear systems with random packet losses in sensor networksen_US
dc.typeArticleen_US
dc.identifier.emailDong, H: shiningdhl@gmail.comen_US
dc.identifier.emailLam, J: james.lam@hku.hk-
dc.identifier.authorityLam, J=rp00133en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1080/00207721.2010.550403en_US
dc.identifier.scopuseid_2-s2.0-79960519555en_US
dc.identifier.hkuros208788-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79960519555&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume42en_US
dc.identifier.issue9en_US
dc.identifier.spage1507en_US
dc.identifier.epage1519en_US
dc.identifier.isiWOS:000292760000007-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridGao, H=7402971422en_US
dc.identifier.scopusauthoridLam, J=7201973414en_US
dc.identifier.scopusauthoridDong, H=15727216900en_US

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