Adaptive Model-Free Formation Control for Multiple-Agent Under Event- Triggered Mechanism
In this article, a distributed model-free mode control strategy combined with event-trigger mechanism is proposed to solve the problem of complex interaction, limited communication range, random link packet loss and unknown dynamics for multi agents cooperation while avoiding obstacle collision. Fir...
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Veröffentlicht in: | IEEE access 2024, Vol.12, p.151178-151187 |
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description | In this article, a distributed model-free mode control strategy combined with event-trigger mechanism is proposed to solve the problem of complex interaction, limited communication range, random link packet loss and unknown dynamics for multi agents cooperation while avoiding obstacle collision. Firstly, the event driven decision-making strategy is established under the conditions, which include random link packet loss or collision event is triggered, which can effectively reduce a large amount of communication and improve resource utilization between agents. Secondly, a random link packet loss compensation mechanism is designed using the output information from neighbors at the time of the previous event trigger. This is then combined with the event-driven communication mechanism to design a distributed control strategy and analyze the convergence performance of the tracking error. Finally, simulation results demonstrate the effectiveness and robustness of proposed control strategy. |
doi_str_mv | 10.1109/ACCESS.2024.3479277 |
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Firstly, the event driven decision-making strategy is established under the conditions, which include random link packet loss or collision event is triggered, which can effectively reduce a large amount of communication and improve resource utilization between agents. Secondly, a random link packet loss compensation mechanism is designed using the output information from neighbors at the time of the previous event trigger. This is then combined with the event-driven communication mechanism to design a distributed control strategy and analyze the convergence performance of the tracking error. Finally, simulation results demonstrate the effectiveness and robustness of proposed control strategy.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2024.3479277</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Adaptive control ; Bandwidth ; Collision avoidance ; Data models ; Decision making ; Error analysis ; Event detection ; Event-triggered ; formation control ; Mathematical models ; Multi-agent systems ; Multiagent systems ; multiple agents system ; obstacle avoidance ; packet dropout ; Packet loss ; Real-time systems ; Resource utilization ; Robust control ; Robustness ; Strategy ; Tracking errors ; Uncertainty ; Vehicle dynamics</subject><ispartof>IEEE access, 2024, Vol.12, p.151178-151187</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c289t-da3b93a28102b28dc2a6af756d410b14cfb479315952f19d75b0892d1e965e3b3</cites><orcidid>0000-0002-8137-5095 ; 0000-0003-4089-7257</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10716364$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,2100,4022,27632,27922,27923,27924,54932</link.rule.ids></links><search><creatorcontrib>Huang, Shixin</creatorcontrib><creatorcontrib>Chen, Xiangjian</creatorcontrib><creatorcontrib>Li, Di</creatorcontrib><title>Adaptive Model-Free Formation Control for Multiple-Agent Under Event- Triggered Mechanism</title><title>IEEE access</title><addtitle>Access</addtitle><description>In this article, a distributed model-free mode control strategy combined with event-trigger mechanism is proposed to solve the problem of complex interaction, limited communication range, random link packet loss and unknown dynamics for multi agents cooperation while avoiding obstacle collision. Firstly, the event driven decision-making strategy is established under the conditions, which include random link packet loss or collision event is triggered, which can effectively reduce a large amount of communication and improve resource utilization between agents. Secondly, a random link packet loss compensation mechanism is designed using the output information from neighbors at the time of the previous event trigger. This is then combined with the event-driven communication mechanism to design a distributed control strategy and analyze the convergence performance of the tracking error. Finally, simulation results demonstrate the effectiveness and robustness of proposed control strategy.</description><subject>Adaptive control</subject><subject>Bandwidth</subject><subject>Collision avoidance</subject><subject>Data models</subject><subject>Decision making</subject><subject>Error analysis</subject><subject>Event detection</subject><subject>Event-triggered</subject><subject>formation control</subject><subject>Mathematical models</subject><subject>Multi-agent systems</subject><subject>Multiagent systems</subject><subject>multiple agents system</subject><subject>obstacle avoidance</subject><subject>packet dropout</subject><subject>Packet loss</subject><subject>Real-time systems</subject><subject>Resource utilization</subject><subject>Robust control</subject><subject>Robustness</subject><subject>Strategy</subject><subject>Tracking errors</subject><subject>Uncertainty</subject><subject>Vehicle dynamics</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1LxDAQLaKgqL9ADwHPXTP5anNcyq4Ku3hQD55C0kzXLN1mTbuC_95qRZzLDI_33szwsuwK6AyA6tt5VS2enmaMMjHjotCsKI6yMwZK51xydfxvPs0u-35LxypHSBZn2evc2_0QPpCso8c2XyZEsoxpZ4cQO1LFbkixJU1MZH1oh7BvMZ9vsBvIS-cxkcXHOOfkOYXNBhN6ssb6zXah311kJ41te7z87efZy3LxXN3nq8e7h2q-ymtW6iH3ljvNLSuBMsdKXzOrbFNI5QVQB6Ju3PgTB6kla0D7QjpaauYBtZLIHT_PHiZfH-3W7FPY2fRpog3mB4hpY2waQt2iaQRK671TvBQCJDjKuEYlmUNBUcPodTN57VN8P2A_mG08pG4833AAXZRKCzay-MSqU-z7hM3fVqDmOxIzRWK-IzG_kYyq60kVEPGfogDFleBfQoiGQw</recordid><startdate>2024</startdate><enddate>2024</enddate><creator>Huang, Shixin</creator><creator>Chen, Xiangjian</creator><creator>Li, Di</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Firstly, the event driven decision-making strategy is established under the conditions, which include random link packet loss or collision event is triggered, which can effectively reduce a large amount of communication and improve resource utilization between agents. Secondly, a random link packet loss compensation mechanism is designed using the output information from neighbors at the time of the previous event trigger. This is then combined with the event-driven communication mechanism to design a distributed control strategy and analyze the convergence performance of the tracking error. Finally, simulation results demonstrate the effectiveness and robustness of proposed control strategy.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2024.3479277</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-8137-5095</orcidid><orcidid>https://orcid.org/0000-0003-4089-7257</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adaptive control Bandwidth Collision avoidance Data models Decision making Error analysis Event detection Event-triggered formation control Mathematical models Multi-agent systems Multiagent systems multiple agents system obstacle avoidance packet dropout Packet loss Real-time systems Resource utilization Robust control Robustness Strategy Tracking errors Uncertainty Vehicle dynamics |
title | Adaptive Model-Free Formation Control for Multiple-Agent Under Event- Triggered Mechanism |
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