Distributed Adaptive Tracking Control for High-Order Nonlinear Multiagent Systems Over Event-Triggered Communication
In this article, we investigate the consensus problem for high-order nonlinear multiagent systems (MASs) with an uncertain leader under event-triggered communication. Compared with the existing consensus results for nonlinear MASs under event-triggered communication, the class of systems considered...
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Veröffentlicht in: | IEEE transactions on automatic control 2023-02, Vol.68 (2), p.1176-1183 |
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description | In this article, we investigate the consensus problem for high-order nonlinear multiagent systems (MASs) with an uncertain leader under event-triggered communication. Compared with the existing consensus results for nonlinear MASs under event-triggered communication, the class of systems considered is more general, while achieving better performance in term of asymptotic tracking. To estimate the unknown parameters of the uncertain leader, distributed intermediate parameter estimators based on event-triggered communication mechanism are first introduced. To guarantee that high-order derivatives exist when applying the backstepping method, such estimators are further modified to obtain final estimators having a polynomial form by using the Hermite interpolation method. Moreover, novel high-order filters are proposed to generate local reference signals and to ensure the existence of high-order derivatives of the filter states. Based on the developed filters, a backstepping-based decentralized adaptive controller is developed. It is proved that consensus errors are asymptotically convergent with the developed method. Finally, simulation examples are provided to show the effectiveness of the proposed method. |
doi_str_mv | 10.1109/TAC.2022.3148384 |
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Compared with the existing consensus results for nonlinear MASs under event-triggered communication, the class of systems considered is more general, while achieving better performance in term of asymptotic tracking. To estimate the unknown parameters of the uncertain leader, distributed intermediate parameter estimators based on event-triggered communication mechanism are first introduced. To guarantee that high-order derivatives exist when applying the backstepping method, such estimators are further modified to obtain final estimators having a polynomial form by using the Hermite interpolation method. Moreover, novel high-order filters are proposed to generate local reference signals and to ensure the existence of high-order derivatives of the filter states. Based on the developed filters, a backstepping-based decentralized adaptive controller is developed. It is proved that consensus errors are asymptotically convergent with the developed method. Finally, simulation examples are provided to show the effectiveness of the proposed method.</description><identifier>ISSN: 0018-9286</identifier><identifier>EISSN: 1558-2523</identifier><identifier>DOI: 10.1109/TAC.2022.3148384</identifier><identifier>CODEN: IETAA9</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive control ; Asymptotic properties ; Backstepping ; Communication ; Estimators ; event-triggered communication ; Interpolation ; Monitoring ; Multiagent systems ; Network topology ; Nonlinear control ; Nonlinear systems ; Parameter estimation ; Parameter uncertainty ; Polynomials ; Reference signals ; Telecommunications ; Tracking control ; uncertain nonlinear systems ; Uncertainty</subject><ispartof>IEEE transactions on automatic control, 2023-02, Vol.68 (2), p.1176-1183</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-db90cbf384b01f2ebedf84bbb70fccdaf22baf9e1cd5bb6553b8c15ab72ff4ab3</citedby><cites>FETCH-LOGICAL-c291t-db90cbf384b01f2ebedf84bbb70fccdaf22baf9e1cd5bb6553b8c15ab72ff4ab3</cites><orcidid>0000-0002-6148-1034 ; 0000-0001-7810-9338 ; 0000-0001-9530-360X ; 0000-0001-8683-3019 ; 0000-0001-9596-2752</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9705094$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9705094$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Deng, Chao</creatorcontrib><creatorcontrib>Wen, Changyun</creatorcontrib><creatorcontrib>Wang, Wei</creatorcontrib><creatorcontrib>Li, Xinyao</creatorcontrib><creatorcontrib>Yue, Dong</creatorcontrib><title>Distributed Adaptive Tracking Control for High-Order Nonlinear Multiagent Systems Over Event-Triggered Communication</title><title>IEEE transactions on automatic control</title><addtitle>TAC</addtitle><description>In this article, we investigate the consensus problem for high-order nonlinear multiagent systems (MASs) with an uncertain leader under event-triggered communication. Compared with the existing consensus results for nonlinear MASs under event-triggered communication, the class of systems considered is more general, while achieving better performance in term of asymptotic tracking. To estimate the unknown parameters of the uncertain leader, distributed intermediate parameter estimators based on event-triggered communication mechanism are first introduced. To guarantee that high-order derivatives exist when applying the backstepping method, such estimators are further modified to obtain final estimators having a polynomial form by using the Hermite interpolation method. Moreover, novel high-order filters are proposed to generate local reference signals and to ensure the existence of high-order derivatives of the filter states. Based on the developed filters, a backstepping-based decentralized adaptive controller is developed. It is proved that consensus errors are asymptotically convergent with the developed method. Finally, simulation examples are provided to show the effectiveness of the proposed method.</description><subject>Adaptive control</subject><subject>Asymptotic properties</subject><subject>Backstepping</subject><subject>Communication</subject><subject>Estimators</subject><subject>event-triggered communication</subject><subject>Interpolation</subject><subject>Monitoring</subject><subject>Multiagent systems</subject><subject>Network topology</subject><subject>Nonlinear control</subject><subject>Nonlinear systems</subject><subject>Parameter estimation</subject><subject>Parameter uncertainty</subject><subject>Polynomials</subject><subject>Reference signals</subject><subject>Telecommunications</subject><subject>Tracking control</subject><subject>uncertain nonlinear systems</subject><subject>Uncertainty</subject><issn>0018-9286</issn><issn>1558-2523</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kM1LwzAYxoMoOKd3wUvAc2eSNmt6HHU6YbqD9VySNKmZbTOTdLD_3owNT-8Hv-d5eR8A7jGaYYyKp2pRzggiZJbijKUsuwATTClLCCXpJZgghFlSEDa_Bjfeb-M4zzI8AeHZ-OCMGINq4KLhu2D2ClaOyx8ztLC0Q3C2g9o6uDLtd7JxjXLwww6dGRR38H3sguGtGgL8PPigeg83-0gs93GVVM60rXLRurR9Pw5G8mDscAuuNO-8ujvXKfh6WVblKllvXt_KxTqRpMAhaUSBpNDxGYGwJkqoRsdeiBxpKRuuCRFcFwrLhgoxpzQVTGLKRU60zrhIp-Dx5Ltz9ndUPtRbO7ohnqxJnmOaEsZwpNCJks5675Sud8703B1qjOpjtnXMtj5mW5-zjZKHk8Qopf7xIkcUFVn6B4wCeOA</recordid><startdate>20230201</startdate><enddate>20230201</enddate><creator>Deng, Chao</creator><creator>Wen, Changyun</creator><creator>Wang, Wei</creator><creator>Li, Xinyao</creator><creator>Yue, Dong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Adaptive control Asymptotic properties Backstepping Communication Estimators event-triggered communication Interpolation Monitoring Multiagent systems Network topology Nonlinear control Nonlinear systems Parameter estimation Parameter uncertainty Polynomials Reference signals Telecommunications Tracking control uncertain nonlinear systems Uncertainty |
title | Distributed Adaptive Tracking Control for High-Order Nonlinear Multiagent Systems Over Event-Triggered Communication |
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