Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105534
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dc.contributorDepartment of Computing-
dc.creatorWu, H-
dc.creatorYang, Z-
dc.creatorCao, J-
dc.creatorLai, L-
dc.date.accessioned2024-04-15T07:34:54Z-
dc.date.available2024-04-15T07:34:54Z-
dc.identifier.issn0018-9545-
dc.identifier.urihttp://hdl.handle.net/10397/105534-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication H. Wu, Z. Yang, J. Cao and L. Lai, "TRiForm: Formation Control for Underwater Sensor Networks With Measurement Errors," in IEEE Transactions on Vehicular Technology, vol. 69, no. 7, pp. 7679-7691, July 2020 is available at https://doi.org/10.1109/TVT.2020.2989363.en_US
dc.subjectFormation Controlen_US
dc.subjectGraph Rigidityen_US
dc.subjectLocalizationen_US
dc.subjectMobile Sensor Nodeen_US
dc.subjectUnderwater Wireless Sensor Networksen_US
dc.titleTRiForm : formation control for underwater sensor networks with measurement errorsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage7679-
dc.identifier.epage7691-
dc.identifier.volume69-
dc.identifier.issue7-
dc.identifier.doi10.1109/TVT.2020.2989363-
dcterms.abstractThe formation control of mobile underwater wireless sensor networks (MUWSNs) is difficult due to the severe errors in distance and motion measurements. To address this problem, we propose a distributed formation control scheme, TRiForm (Triangle Formation). TRiForm constructs a virtual structure that is a rigid graph formed by triangles of nodes in an MUWSN for high reliability and efficiency in formation control. Furthermore, it utilizes the anchor information to detect and to compensate for measurement errors. We have proven the correctness of the rigidity graph construction by TRiForm. We have also evaluated TRiForm in various scenarios using simulation with the measured parameters from real underwater sensor nodes. The results show that TRiForm can successfully maintain the formations of an MUWSN and control the MUWSN to reach the predefined destination under distance and motion measurement errors.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on vehicular technology, July 2020, v. 69, no. 7, p. 7679-7691-
dcterms.isPartOfIEEE transactions on vehicular technology-
dcterms.issued2020-07-
dc.identifier.scopus2-s2.0-85088500238-
dc.identifier.eissn1939-9359-
dc.description.validate202402 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCOMP-0308en_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Key R&D Program of China; National Natural Science Foundation of China (NSFC); Shenzhen Basic Research Funding Scheme; Middleware for Distributed Control and Coordination of Robot Networksen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS43660635en_US
dc.description.oaCategoryGreen (AAM)en_US
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