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Article: A generalized parameter-dependent approach to robust H∞ filtering of stochastic systems

TitleA generalized parameter-dependent approach to robust H∞ filtering of stochastic systems
Authors
KeywordsH∞ Filtering
Linear Matrix Inequality
Robust Filtering
Stochastic Systems
Uncertain Systems
Issue Date2009
PublisherBirkhaeuser Boston. The Journal's web site is located at http://link.springer.de/link/service/journals/00034/
Citation
Circuits, Systems, And Signal Processing, 2009, v. 28 n. 2, p. 191-204 How to Cite?
Abstract
This paper is concerned with the problem of robust H ∞ filtering for discrete-time stochastic systems with state-dependent stochastic noises and deterministic polytopic parameter uncertainties. We utilize the polynomial parameter-dependent approach to solve the robust H ∞ filtering problem, and the proposed approach includes results in the quadratic framework that entail fixed matrices for the entire uncertain domain and results in the linearly parameter-dependent framework that use linear convex combinations of matrices as special cases. New linear matrix inequality (LMI) conditions obtained for the existence of admissible filters are developed based on homogeneous polynomial parameter-dependent matrices of arbitrary degree. As the degree grows, a test of increasing precision is obtained, providing less conservative filter designs. A numerical example is provided to illustrate the effectiveness and advantages of the filter design methods proposed in this paper. © Birkhäuser Boston 2008.
Persistent Identifierhttp://hdl.handle.net/10722/157000
ISSN
2013 Impact Factor: 1.264
2013 SCImago Journal Rankings: 0.447
ISI Accession Number ID
Funding AgencyGrant Number
HKUCRCG 200611159157
National Nature Science Foundation of China60504008
The Research Fund for the Doctoral Programme of Higher Education of China20070213084
Fok Ying Tung Education Foundation111064
Key Laboratory of Integrated Automation for the Process Industry (Northeastern University)
Ministry of Education of China
Funding Information:

This work was supported by HKU CRCG 200611159157, the National Nature Science Foundation of China (60504008), The Research Fund for the Doctoral Programme of Higher Education of China (20070213084), the Fok Ying Tung Education Foundation (111064), and the Key Laboratory of Integrated Automation for the Process Industry (Northeastern University), Ministry of Education of China.

References

 

Author Affiliations
  1. The University of Hong Kong
  2. Harbin Institute of Technology
DC FieldValueLanguage
dc.contributor.authorMeng, Xen_US
dc.contributor.authorLam, Jen_US
dc.contributor.authorFei, Zen_US
dc.date.accessioned2012-08-08T08:44:53Z-
dc.date.available2012-08-08T08:44:53Z-
dc.date.issued2009en_US
dc.identifier.citationCircuits, Systems, And Signal Processing, 2009, v. 28 n. 2, p. 191-204en_US
dc.identifier.issn0278-081Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/157000-
dc.description.abstractThis paper is concerned with the problem of robust H ∞ filtering for discrete-time stochastic systems with state-dependent stochastic noises and deterministic polytopic parameter uncertainties. We utilize the polynomial parameter-dependent approach to solve the robust H ∞ filtering problem, and the proposed approach includes results in the quadratic framework that entail fixed matrices for the entire uncertain domain and results in the linearly parameter-dependent framework that use linear convex combinations of matrices as special cases. New linear matrix inequality (LMI) conditions obtained for the existence of admissible filters are developed based on homogeneous polynomial parameter-dependent matrices of arbitrary degree. As the degree grows, a test of increasing precision is obtained, providing less conservative filter designs. A numerical example is provided to illustrate the effectiveness and advantages of the filter design methods proposed in this paper. © Birkhäuser Boston 2008.en_US
dc.languageengen_US
dc.publisherBirkhaeuser Boston. The Journal's web site is located at http://link.springer.de/link/service/journals/00034/en_US
dc.relation.ispartofCircuits, Systems, and Signal Processingen_US
dc.subjectH∞ Filteringen_US
dc.subjectLinear Matrix Inequalityen_US
dc.subjectRobust Filteringen_US
dc.subjectStochastic Systemsen_US
dc.subjectUncertain Systemsen_US
dc.titleA generalized parameter-dependent approach to robust H∞ filtering of stochastic systemsen_US
dc.typeArticleen_US
dc.identifier.emailLam, J:james.lam@hku.hken_US
dc.identifier.authorityLam, J=rp00133en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/s00034-008-9084-1en_US
dc.identifier.scopuseid_2-s2.0-63649135097en_US
dc.identifier.hkuros164250-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-63649135097&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume28en_US
dc.identifier.issue2en_US
dc.identifier.spage191en_US
dc.identifier.epage204en_US
dc.identifier.isiWOS:000264517600002-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridMeng, X=22735068600en_US
dc.identifier.scopusauthoridLam, J=7201973414en_US
dc.identifier.scopusauthoridFei, Z=24766310700en_US
dc.identifier.citeulike3609185-

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