Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/154201
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dc.contributor.authorZhang, Y.en_US
dc.contributor.authorSun, L.en_US
dc.contributor.authorHu, Guoqiangen_US
dc.date.accessioned2021-12-16T02:38:58Z-
dc.date.available2021-12-16T02:38:58Z-
dc.date.issued2020-
dc.identifier.citationZhang, Y., Sun, L. & Hu, G. (2020). Distributed consensus-based multitarget filtering and its application in formation-containment control. IEEE Transactions On Control of Network Systems, 7(1), 503-515. https://dx.doi.org/10.1109/TCNS.2019.2926281en_US
dc.identifier.issn2325-5870en_US
dc.identifier.urihttps://hdl.handle.net/10356/154201-
dc.description.abstractThis paper studies a distributed multitarget filtering problem for a sensor network where each sensor can obtain the measurements and system information of some targets while having no knowledge of others. To estimate the states of all targets, a consensus Kalman information filtering algorithm with an adaptive and finite-time matrix-weighted consensus strategy is proposed. When the communication network is strongly connected and the sensing network is time-varying while being always collectively observable, it is proved that if the targets' system matrices are time invariant, the mean-square estimation errors of the sensors are bounded for any number of consensus iterations. If the targets' system matrices are time varying and the number of the consensus steps per information filtering is larger than the diameter of the communication topology, the mean-square estimation errors of the sensors are also bounded. When each sensor is intermittently activated to observe the targets and the network does not remain collectively observable, an allowable lower bound of detection probability is derived to guarantee the stochastic boundedness of the estimation errors. Then, the filtering algorithm is applied to design a distributed containment controller for multiple agents to encircle multiple planar heterogeneous dynamic targets. Finally, simulation examples are given to illustrate the effectiveness of the algorithms.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.language.isoenen_US
dc.relationRG180/17(2017-T1-002- 158)en_US
dc.relation.ispartofIEEE Transactions on Control of Network Systemsen_US
dc.rights© 2019 IEEE. All rights reserved.en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleDistributed consensus-based multitarget filtering and its application in formation-containment controlen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doi10.1109/TCNS.2019.2926281-
dc.identifier.scopus2-s2.0-85068542593-
dc.identifier.issue1en_US
dc.identifier.volume7en_US
dc.identifier.spage503en_US
dc.identifier.epage515en_US
dc.subject.keywordsContainment Controlen_US
dc.subject.keywordsDistributed Filteringen_US
dc.description.acknowledgementThis work was supported in part by the National Natural Science Foundation (NNSF) of China under Grant 61473081, in part by the Six Talent Peaks Project in Jiangsu Province under Grant XYDXX-005, and in part by the Singapore Ministry of Education Academic Research Fund Tier 1 RG180/17(2017-T1-002- 158). Recommended by Associate Editor L. Schenato.en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
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