File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Robust distributed state estimation for sensor networks with multiple stochastic communication delays

TitleRobust distributed state estimation for sensor networks with multiple stochastic communication delays
Authors
KeywordsDistributed state estimation
Kronecker product
Robust estimation
Stochastic communication delays
Stochastic perturbation
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. 1459-1471 How to Cite?
AbstractThis article is concerned with the robust distributed state estimation problem for a class of uncertain sensor networks with multiple stochastic communication delays. A sequence of mutually independent random variables obeying the Bernoulli distribution is introduced to account for the randomly occurred communication delays. Both the discrete-time target plant and the sensor model are subject to parameter uncertainties as well as stochastic disturbance. The parameter uncertainties are norm-bounded and enter both the system and the measurement matrices. The external stochastic disturbance is given in the form of a scalar Wiener process. Through available output measurements from not only each individual sensor but also its neighbouring sensors, we aim to design distributed state estimators in order to approximate the state of the target plant. By using the Kronecker product, stochastic analysis is carried out to derive a sufficient criterion ensuring the estimation error systems to be convergent in the mean square sense for all randomly occurred delays, admissible stochastic disturbance and parameter uncertainties. Then, an explicit expression of the individual estimator is given in terms of the solution to a convex optimisation problem that can be easily solved by using the semi-definite programme method. A numerical example is given at the end of this article to demonstrate the usefulness of the developed theoretical results. © 2011 Taylor & Francis.
Persistent Identifierhttp://hdl.handle.net/10722/157131
ISSN
2015 Impact Factor: 1.947
2015 SCImago Journal Rankings: 1.083
ISI Accession Number ID
Funding AgencyGrant Number
Royal Society of the UK
University of Hong KongHKU/CRCG/200907176129
National Natural Science Foundation of China60804028
61004067
Specialised Research Fund for the Doctoral Program of Higher Education for New Teachers in China200802861044
Southeast University of China
Youth Science Fund of Heilongjiang Province of ChinaQC2009C63
Funding Information:

This work was supported in part by the Royal Society of the UK, the University of Hong Kong under Grant No. HKU/CRCG/200907176129, the National Natural Science Foundation of China under Grant Nos. 60804028 and 61004067, the Specialised Research Fund for the Doctoral Program of Higher Education for New Teachers in China under Grant No. 200802861044, the Teaching and Research Fund for Excellent Young Teachers at Southeast University of China and the Youth Science Fund of Heilongjiang Province of China under Grant No. QC2009C63.

References

 

DC FieldValueLanguage
dc.contributor.authorLiang, Jen_US
dc.contributor.authorShen, Ben_US
dc.contributor.authorDong, Hen_US
dc.contributor.authorLam, Jen_US
dc.date.accessioned2012-08-08T08:45:27Z-
dc.date.available2012-08-08T08:45:27Z-
dc.date.issued2011en_US
dc.identifier.citationInternational Journal of Systems Science, 2011, v. 42 n. 9, p. 1459-1471en_US
dc.identifier.issn0020-7721en_US
dc.identifier.urihttp://hdl.handle.net/10722/157131-
dc.description.abstractThis article is concerned with the robust distributed state estimation problem for a class of uncertain sensor networks with multiple stochastic communication delays. A sequence of mutually independent random variables obeying the Bernoulli distribution is introduced to account for the randomly occurred communication delays. Both the discrete-time target plant and the sensor model are subject to parameter uncertainties as well as stochastic disturbance. The parameter uncertainties are norm-bounded and enter both the system and the measurement matrices. The external stochastic disturbance is given in the form of a scalar Wiener process. Through available output measurements from not only each individual sensor but also its neighbouring sensors, we aim to design distributed state estimators in order to approximate the state of the target plant. By using the Kronecker product, stochastic analysis is carried out to derive a sufficient criterion ensuring the estimation error systems to be convergent in the mean square sense for all randomly occurred delays, admissible stochastic disturbance and parameter uncertainties. Then, an explicit expression of the individual estimator is given in terms of the solution to a convex optimisation problem that can be easily solved by using the semi-definite programme method. A numerical example is given at the end of this article to demonstrate the usefulness 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.subjectDistributed state estimationen_US
dc.subjectKronecker producten_US
dc.subjectRobust estimationen_US
dc.subjectStochastic communication delaysen_US
dc.subjectStochastic perturbationen_US
dc.titleRobust distributed state estimation for sensor networks with multiple stochastic communication delaysen_US
dc.typeArticleen_US
dc.identifier.emailLiang, J: jinlliang@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.doi10.1080/00207721.2010.550402en_US
dc.identifier.scopuseid_2-s2.0-79960490958en_US
dc.identifier.hkuros208791-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79960490958&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume42en_US
dc.identifier.issue9en_US
dc.identifier.spage1459en_US
dc.identifier.epage1471en_US
dc.identifier.isiWOS:000292760000004-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridLam, J=7201973414en_US
dc.identifier.scopusauthoridDong, H=15727216900en_US
dc.identifier.scopusauthoridShen, B=36158783600en_US
dc.identifier.scopusauthoridLiang, J=24544407400en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats