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Article: Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case
Title | Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case | ||||||||
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Authors | |||||||||
Keywords | Data missing Difference linear matrix inequalities Discrete time-varying systems Distributed H∞-consensus filtering Finite-horizon Sensor networks | ||||||||
Issue Date | 2010 | ||||||||
Publisher | Pergamon. 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? | ||||||||
Abstract | This 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 Identifier | http://hdl.handle.net/10722/135624 | ||||||||
ISSN | 2023 Impact Factor: 4.8 2023 SCImago Journal Rankings: 3.502 | ||||||||
ISI Accession Number ID |
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 Field | Value | Language |
---|---|---|
dc.contributor.author | Shen, B | en_HK |
dc.contributor.author | Wang, Z | en_HK |
dc.contributor.author | Hung, YS | en_HK |
dc.date.accessioned | 2011-07-27T01:37:45Z | - |
dc.date.available | 2011-07-27T01:37:45Z | - |
dc.date.issued | 2010 | en_HK |
dc.identifier.citation | Automatica, 2010, v. 46 n. 10, p. 1682-1688 | en_HK |
dc.identifier.issn | 0005-1098 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/135624 | - |
dc.description.abstract | This 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.language | eng | en_US |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/automatica | en_HK |
dc.relation.ispartof | Automatica | en_HK |
dc.subject | Data missing | en_HK |
dc.subject | Difference linear matrix inequalities | en_HK |
dc.subject | Discrete time-varying systems | en_HK |
dc.subject | Distributed H∞-consensus filtering | en_HK |
dc.subject | Finite-horizon | en_HK |
dc.subject | Sensor networks | en_HK |
dc.title | Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://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.email | Hung, YS:yshung@eee.hku.hk | en_HK |
dc.identifier.authority | Hung, YS=rp00220 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.automatica.2010.06.025 | en_HK |
dc.identifier.scopus | eid_2-s2.0-77956420057 | en_HK |
dc.identifier.hkuros | 187892 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-77956420057&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 46 | en_HK |
dc.identifier.issue | 10 | en_HK |
dc.identifier.spage | 1682 | en_HK |
dc.identifier.epage | 1688 | en_HK |
dc.identifier.isi | WOS:000282620600011 | - |
dc.publisher.place | United Kingdom | en_HK |
dc.identifier.scopusauthorid | Shen, B=36158783600 | en_HK |
dc.identifier.scopusauthorid | Wang, Z=7410037481 | en_HK |
dc.identifier.scopusauthorid | Hung, YS=8091656200 | en_HK |
dc.identifier.citeulike | 7586503 | - |
dc.identifier.issnl | 0005-1098 | - |