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  Event-Triggered Adaptive Containment Control for Heterogeneous Stochastic Nonlinear Multiagent Systems

Wang, X., Xu, R., Huang, T., & Kurths, J. (2024). Event-Triggered Adaptive Containment Control for Heterogeneous Stochastic Nonlinear Multiagent Systems. IEEE Transactions on Neural Networks and Learning Systems, 35(6), 8524-8534. doi:10.1109/TNNLS.2022.3230508.

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資料種別: 学術論文

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 作成者:
Wang, Xin 1, 著者
Xu, Rui 1, 著者
Huang, Tingwen 1, 著者
Kurths, Jürgen2, 著者              
所属:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 要旨: This article investigates the event-triggered adaptive containment control problem for a class of stochastic nonlinear multiagent systems with unmeasurable states. A stochastic system with unknown heterogeneous dynamics is established to describe the agents in a random vibration environment. Besides, the uncertain nonlinear dynamics are approximated by radial basis function neural networks (NNs), and the unmeasured states are estimated by constructing the NN-based observer. In addition, the switching-threshold-based event-triggered control method is adopted with the hope of reducing communication consumption and balancing system performance and network constraints. Moreover, we develop the novel distributed containment controller by utilizing the adaptive backstepping control strategy and the dynamic surface control (DSC) approach such that the output of each follower converges to the convex hull spanned by multiple leaders, and all signals of the closed-loop system are cooperatively semi-globally uniformly ultimately bounded in mean square. Finally, we verify the efficiency of the proposed controller by the simulation examples.

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言語: eng - 英語
 日付: 2023-01-032024-06-01
 出版の状態: Finally published
 ページ: -
 出版情報: -
 目次: -
 査読: 査読あり
 識別子(DOI, ISBNなど): DOI: 10.1109/TNNLS.2022.3230508
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning
 学位: -

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出版物 1

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出版物名: IEEE Transactions on Neural Networks and Learning Systems
種別: 学術雑誌, SCI, Scopus
 著者・編者:
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出版社, 出版地: -
ページ: - 巻号: 35 (6) 通巻号: - 開始・終了ページ: 8524 - 8534 識別子(ISBN, ISSN, DOIなど): CoNE: https://publications.pik-potsdam.de/cone/journals/resource/IEEE-transactions-on-neural-networks-and-learning-systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)