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Article: Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case

TitleDistributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case
Authors
KeywordsData missing
Difference linear matrix inequalities
Discrete time-varying systems
Distributed H∞-consensus filtering
Finite-horizon
Sensor networks
Issue Date2010
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/automatica
Citation
Automatica, 2010, v. 46 n. 10, p. 1682-1688 How to Cite?
AbstractThis paper is concerned with a new distributed H∞-consensus filtering problem over a finite-horizon for sensor networks with multiple missing measurements. The so-called H∞-consensus performance requirement is defined to quantify bounded consensus regarding the filtering errors (agreements) over a finite-horizon. A set of random variables are utilized to model the probabilistic information missing phenomena occurring in the channels from the system to the sensors. A sufficient condition is first established in terms of a set of difference linear matrix inequalities (DLMIs) under which the expected H∞-consensus performance constraint is guaranteed. Given the measurements and estimates of the system state and its neighbors, the filter parameters are then explicitly parameterized by means of the solutions to a certain set of DLMIs that can be computed recursively. Subsequently, two kinds of robust distributed H∞-consensus filters are designed for the system with norm-bounded uncertainties and polytopic uncertainties. Finally, two numerical simulation examples are used to demonstrate the effectiveness of the proposed distributed filters design scheme. © 2010 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/135624
ISSN
2015 Impact Factor: 3.635
2015 SCImago Journal Rankings: 4.315
ISI Accession Number ID
Funding AgencyGrant Number
Engineering and Physical Sciences Research Council (EPSRC) of the UKGR/S27658/01
Royal Society of the UK
Alexander von Humboldt Foundation of Germany
Funding Information:

This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany. The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Masayuki Fujita under the direction of Editor Ian R. Petersen.

References

 

DC FieldValueLanguage
dc.contributor.authorShen, Ben_HK
dc.contributor.authorWang, Zen_HK
dc.contributor.authorHung, YSen_HK
dc.date.accessioned2011-07-27T01:37:45Z-
dc.date.available2011-07-27T01:37:45Z-
dc.date.issued2010en_HK
dc.identifier.citationAutomatica, 2010, v. 46 n. 10, p. 1682-1688en_HK
dc.identifier.issn0005-1098en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135624-
dc.description.abstractThis paper is concerned with a new distributed H∞-consensus filtering problem over a finite-horizon for sensor networks with multiple missing measurements. The so-called H∞-consensus performance requirement is defined to quantify bounded consensus regarding the filtering errors (agreements) over a finite-horizon. A set of random variables are utilized to model the probabilistic information missing phenomena occurring in the channels from the system to the sensors. A sufficient condition is first established in terms of a set of difference linear matrix inequalities (DLMIs) under which the expected H∞-consensus performance constraint is guaranteed. Given the measurements and estimates of the system state and its neighbors, the filter parameters are then explicitly parameterized by means of the solutions to a certain set of DLMIs that can be computed recursively. Subsequently, two kinds of robust distributed H∞-consensus filters are designed for the system with norm-bounded uncertainties and polytopic uncertainties. Finally, two numerical simulation examples are used to demonstrate the effectiveness of the proposed distributed filters design scheme. © 2010 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_US
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/automaticaen_HK
dc.relation.ispartofAutomaticaen_HK
dc.subjectData missingen_HK
dc.subjectDifference linear matrix inequalitiesen_HK
dc.subjectDiscrete time-varying systemsen_HK
dc.subjectDistributed H∞-consensus filteringen_HK
dc.subjectFinite-horizonen_HK
dc.subjectSensor networksen_HK
dc.titleDistributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon caseen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0005-1098&volume=46&issue=10&spage=1682&epage=1688&date=2010&atitle=Distributed+H∞-consensus+filtering+in+sensor+networks+with+multiple+missing+measurements:+the+finite-horizon+case-
dc.identifier.emailHung, YS:yshung@eee.hku.hken_HK
dc.identifier.authorityHung, YS=rp00220en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.automatica.2010.06.025en_HK
dc.identifier.scopuseid_2-s2.0-77956420057en_HK
dc.identifier.hkuros187892en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77956420057&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume46en_HK
dc.identifier.issue10en_HK
dc.identifier.spage1682en_HK
dc.identifier.epage1688en_HK
dc.identifier.isiWOS:000282620600011-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridShen, B=36158783600en_HK
dc.identifier.scopusauthoridWang, Z=7410037481en_HK
dc.identifier.scopusauthoridHung, YS=8091656200en_HK
dc.identifier.citeulike7586503-

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