Consensus of Linear Multiagent Systems With Input-Based Triggering Condition
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Xu, Yong | - |
dc.contributor.author | Wu, Zheng-Guang | - |
dc.contributor.author | Pan, Ya-Jun | - |
dc.contributor.author | Ahn, Choon Ki | - |
dc.contributor.author | Yan, Huaicheng | - |
dc.date.accessioned | 2021-09-01T01:21:45Z | - |
dc.date.available | 2021-09-01T01:21:45Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2019-11 | - |
dc.identifier.issn | 2168-2216 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/62055 | - |
dc.description.abstract | This paper considers the consensus problem of multiagent systems with the input-based triggering condition. A model-based approach is first given to estimate the relative interagent states between intermittent communications instead of absolute states. A novel consensus protocol consisting of the relative interagent states is proposed for the consensus problem. Besides, compared with some results on the triggering condition consisting of state measurement error, a new triggering condition is constructed based on the control input. Then, the consensus protocol is executed by every agent in a fully distributed way, which has the advantage that the controller design is related to the number of agents instead of using global information. Moreover, the bounds of parameters of the controller and the triggering condition can be obtained by the proposed algorithm simultaneously, which depends on the total number of agents in multiagent networks. The proposed control scheme can ensure that states of all agents can achieve consensus. It is shown that "Zeno behavior" does not appear under the proposed algorithm. Finally, an illustrative example is given to verify the proposed method. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | STABILITY ANALYSIS | - |
dc.subject | EXPONENTIAL STABILITY | - |
dc.subject | TRACKING CONTROL | - |
dc.subject | EVENT | - |
dc.subject | NETWORKS | - |
dc.subject | LEADER | - |
dc.title | Consensus of Linear Multiagent Systems With Input-Based Triggering Condition | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ahn, Choon Ki | - |
dc.identifier.doi | 10.1109/TSMC.2018.2853809 | - |
dc.identifier.scopusid | 2-s2.0-85050633585 | - |
dc.identifier.wosid | 000501863500010 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, v.49, no.11, pp.2308 - 2317 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | - |
dc.citation.title | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | - |
dc.citation.volume | 49 | - |
dc.citation.number | 11 | - |
dc.citation.startPage | 2308 | - |
dc.citation.endPage | 2317 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Cybernetics | - |
dc.subject.keywordPlus | STABILITY ANALYSIS | - |
dc.subject.keywordPlus | EXPONENTIAL STABILITY | - |
dc.subject.keywordPlus | TRACKING CONTROL | - |
dc.subject.keywordPlus | EVENT | - |
dc.subject.keywordPlus | NETWORKS | - |
dc.subject.keywordPlus | LEADER | - |
dc.subject.keywordAuthor | Consensus | - |
dc.subject.keywordAuthor | event-triggered control (ETC) | - |
dc.subject.keywordAuthor | multiagent systems (MASs) | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.