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Decision and Event-Based Fixed-Time Consensus Control for Electromagnetic Source Localization

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dc.contributor.authorLu, Qiang-
dc.contributor.authorHan, Qing-Long-
dc.contributor.authorPeng, Dongliang-
dc.contributor.authorChoi, Youngjin-
dc.date.accessioned2022-07-18T01:16:51Z-
dc.date.available2022-07-18T01:16:51Z-
dc.date.issued2022-04-
dc.identifier.issn2168-2267-
dc.identifier.issn2168-2275-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/107896-
dc.description.abstractThis article deals with the problem of electromagnetic source localization (ESL). An evolutionary particle filter, which is first used to make a decision on the positions of electromagnetic sources, has two characteristics. One characteristic is that the number of particles can be significantly reduced while the other characteristic is that the particle diversity can be well improved. On the basis of the estimated positions of electromagnetic sources, the position and velocity of the virtual leader can be determined. Then, an event-based fixed-time consensus control approach is proposed such that the positions and velocities of robots reach consensus with the virtual leader over a fixed-time interval while saving resource consumption by reducing the communication frequencies and updating times of control inputs. Finally, simulation and experimental results show the effectiveness of the proposed decision and event-based fixed-time consensus control approach for ESL.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherIEEE Advancing Technology for Humanity-
dc.titleDecision and Event-Based Fixed-Time Consensus Control for Electromagnetic Source Localization-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1109/TCYB.2020.3005964-
dc.identifier.scopusid2-s2.0-85128245282-
dc.identifier.wosid000778931500021-
dc.identifier.bibliographicCitationIEEE Transactions on Cybernetics, v.52, no.4, pp 2186 - 2199-
dc.citation.titleIEEE Transactions on Cybernetics-
dc.citation.volume52-
dc.citation.number4-
dc.citation.startPage2186-
dc.citation.endPage2199-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaAutomation & Control Systems-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryAutomation & Control Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Cybernetics-
dc.subject.keywordPlusMULTIAGENT SYSTEMS-
dc.subject.keywordPlusTRIGGERED CONTROL-
dc.subject.keywordPlusMOBILE ROBOTS-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlusNETWORKS-
dc.subject.keywordAuthorElectromagnetics-
dc.subject.keywordAuthorMulti-agent systems-
dc.subject.keywordAuthorRobot kinematics-
dc.subject.keywordAuthorConvergence-
dc.subject.keywordAuthorMulti-robot systems-
dc.subject.keywordAuthorReal-time systems-
dc.subject.keywordAuthorElectromagnetic sources-
dc.subject.keywordAuthorevent-based communication-
dc.subject.keywordAuthorfixed-time control-
dc.subject.keywordAuthormultiple mobile robots-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/9152097-
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