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Article: Distributed H ∞ filtering for polynomial nonlinear stochastic systems in sensor networks

TitleDistributed H ∞ filtering for polynomial nonlinear stochastic systems in sensor networks
Authors
KeywordsDistributed H∞ filtering
Parameter-dependent linear matrix inequalities (PDLMIS)
Polynomial systems
Sensor networks
Stochastic systems
Sum of squares (Sos)
Issue Date2011
PublisherIEEE. The Journal's web site is located at http://www.ewh.ieee.org/soc/ies/ties/index.html
Citation
IEEE Transactions on Industrial Electronics, 2011, v. 58 n. 5, p. 1971-1979 How to Cite?
AbstractIn this paper, the distributed H∞ filtering problem is addressed for a class of polynomial nonlinear stochastic systems in sensor networks. For a Lyapunov function candidate whose entries are polynomials, we calculate its first- and second-order derivatives in order to facilitate the use of Itô's differential rule. Then, a sufficient condition for the existence of a feasible solution to the addressed distributed H∞ filtering problem is derived in terms of parameter-dependent linear matrix inequalities (PDLMIs). For computational convenience, these PDLMIs are further converted into a set of sums of squares that can be solved effectively by using the semidefinite programming technique. Finally, a numerical simulation example is provided to demonstrate the effectiveness and applicability of the proposed design approach.
Persistent Identifierhttp://hdl.handle.net/10722/135119
ISSN
2015 Impact Factor: 6.383
2015 SCImago Journal Rankings: 3.285
ISI Accession Number ID
Funding AgencyGrant Number
Engineering and Physical Sciences Research Council of the U.K.GR/S27658/01
Royal Society of the U.K.
National 973 Program of China2009CB320600
National Natural Science Foundation of China60974030
Alexander von Humboldt Foundation of Germany
Funding Information:

Manuscript received January 27, 2010; revised April 2, 2010; accepted June 1, 2010. Date of publication June 21, 2010; date of current version April 13, 2011. This work was supported in part by the Engineering and Physical Sciences Research Council of the U.K. under Grant GR/S27658/01, by the Royal Society of the U.K., by the National 973 Program of China under Grant 2009CB320600, by the National Natural Science Foundation of China under Grant 60974030, and by the Alexander von Humboldt Foundation of Germany.

References

 

DC FieldValueLanguage
dc.contributor.authorShen, Ben_US
dc.contributor.authorWang, Zen_US
dc.contributor.authorHung, YSen_US
dc.contributor.authorChesi, Gen_US
dc.date.accessioned2011-07-27T01:28:32Z-
dc.date.available2011-07-27T01:28:32Z-
dc.date.issued2011en_US
dc.identifier.citationIEEE Transactions on Industrial Electronics, 2011, v. 58 n. 5, p. 1971-1979en_US
dc.identifier.issn0278-0046-
dc.identifier.urihttp://hdl.handle.net/10722/135119-
dc.description.abstractIn this paper, the distributed H∞ filtering problem is addressed for a class of polynomial nonlinear stochastic systems in sensor networks. For a Lyapunov function candidate whose entries are polynomials, we calculate its first- and second-order derivatives in order to facilitate the use of Itô's differential rule. Then, a sufficient condition for the existence of a feasible solution to the addressed distributed H∞ filtering problem is derived in terms of parameter-dependent linear matrix inequalities (PDLMIs). For computational convenience, these PDLMIs are further converted into a set of sums of squares that can be solved effectively by using the semidefinite programming technique. Finally, a numerical simulation example is provided to demonstrate the effectiveness and applicability of the proposed design approach.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://www.ewh.ieee.org/soc/ies/ties/index.html-
dc.relation.ispartofIEEE Transactions on Industrial Electronicsen_US
dc.rightsIEEE Transactions on Industrial Electronics. Copyright © IEEE.-
dc.rights©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectDistributed H∞ filtering-
dc.subjectParameter-dependent linear matrix inequalities (PDLMIS)-
dc.subjectPolynomial systems-
dc.subjectSensor networks-
dc.subjectStochastic systems-
dc.subjectSum of squares (Sos)-
dc.titleDistributed H ∞ filtering for polynomial nonlinear stochastic systems in sensor networksen_US
dc.typeArticleen_US
dc.identifier.emailHung, YS: yshung@eee.hku.hken_US
dc.identifier.emailChesi, G: chesi@eee.hku.hken_US
dc.identifier.authorityHung, YS=rp00220en_US
dc.identifier.authorityChesi, G=rp00100en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/TIE.2010.2053339-
dc.identifier.scopuseid_2-s2.0-79954529650-
dc.identifier.hkuros187532en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79954529650&selection=ref&src=s&origin=recordpage-
dc.identifier.volume58en_US
dc.identifier.issue5-
dc.identifier.spage1971en_US
dc.identifier.epage1979en_US
dc.identifier.isiWOS:000289478000048-
dc.publisher.placeUnited States-
dc.identifier.scopusauthoridShen, B=36158783600-
dc.identifier.scopusauthoridWang, Z=35231712300-
dc.identifier.scopusauthoridHung, YS=8091656200-
dc.identifier.scopusauthoridChesi, G=7006328614-

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