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Article: Distributed H ∞ filtering for polynomial nonlinear stochastic systems in sensor networks
| Title | Distributed H ∞ filtering for polynomial nonlinear stochastic systems in sensor networks | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Authors | |||||||||||||
| Keywords | Distributed H∞ filtering Parameter-dependent linear matrix inequalities (PDLMIS) Polynomial systems Sensor networks Stochastic systems Sum of squares (Sos) | ||||||||||||
| Issue Date | 2011 | ||||||||||||
| Publisher | IEEE. 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? | ||||||||||||
| Abstract | In 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 Identifier | http://hdl.handle.net/10722/135119 | ||||||||||||
| ISSN | 2023 Impact Factor: 7.5 2023 SCImago Journal Rankings: 3.395 | ||||||||||||
| ISI Accession Number ID |
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 Field | Value | Language |
|---|---|---|
| dc.contributor.author | Shen, B | en_US |
| dc.contributor.author | Wang, Z | en_US |
| dc.contributor.author | Hung, YS | en_US |
| dc.contributor.author | Chesi, G | en_US |
| dc.date.accessioned | 2011-07-27T01:28:32Z | - |
| dc.date.available | 2011-07-27T01:28:32Z | - |
| dc.date.issued | 2011 | en_US |
| dc.identifier.citation | IEEE Transactions on Industrial Electronics, 2011, v. 58 n. 5, p. 1971-1979 | en_US |
| dc.identifier.issn | 0278-0046 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/135119 | - |
| dc.description.abstract | In 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.language | eng | en_US |
| dc.publisher | IEEE. The Journal's web site is located at http://www.ewh.ieee.org/soc/ies/ties/index.html | - |
| dc.relation.ispartof | IEEE Transactions on Industrial Electronics | en_US |
| dc.rights | ©2010 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.subject | Distributed H∞ filtering | - |
| dc.subject | Parameter-dependent linear matrix inequalities (PDLMIS) | - |
| dc.subject | Polynomial systems | - |
| dc.subject | Sensor networks | - |
| dc.subject | Stochastic systems | - |
| dc.subject | Sum of squares (Sos) | - |
| dc.title | Distributed H ∞ filtering for polynomial nonlinear stochastic systems in sensor networks | en_US |
| dc.type | Article | en_US |
| dc.identifier.email | Hung, YS: yshung@eee.hku.hk | en_US |
| dc.identifier.email | Chesi, G: chesi@eee.hku.hk | en_US |
| dc.identifier.authority | Hung, YS=rp00220 | en_US |
| dc.identifier.authority | Chesi, G=rp00100 | en_US |
| dc.description.nature | published_or_final_version | - |
| dc.identifier.doi | 10.1109/TIE.2010.2053339 | - |
| dc.identifier.scopus | eid_2-s2.0-79954529650 | - |
| dc.identifier.hkuros | 187532 | en_US |
| dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-79954529650&selection=ref&src=s&origin=recordpage | - |
| dc.identifier.volume | 58 | en_US |
| dc.identifier.issue | 5 | - |
| dc.identifier.spage | 1971 | en_US |
| dc.identifier.epage | 1979 | en_US |
| dc.identifier.isi | WOS:000289478000048 | - |
| dc.publisher.place | United States | - |
| dc.identifier.scopusauthorid | Shen, B=36158783600 | - |
| dc.identifier.scopusauthorid | Wang, Z=35231712300 | - |
| dc.identifier.scopusauthorid | Hung, YS=8091656200 | - |
| dc.identifier.scopusauthorid | Chesi, G=7006328614 | - |
| dc.identifier.issnl | 0278-0046 | - |