Data-driven-based fully distributed event-triggered control for nonlinear multi-agent systems

Xiaojie Qiu, Wenchao Meng, Yingchun Wang and Qinmin Yang

Applied Mathematics and Computation, 2025, vol. 495, issue C

Abstract: This paper investigates the fully distributed control issue for nonlinear multi-agent systems (MASs) under the limited network bandwidth. A novel event-triggered MFAC framework is developed to ensure the consensus of system output signals in a fully distributed manner, in which an adaptive step-size operator is introduced to eliminate the reliance on communication topology information. To save communication resources efficiently, a dynamic event-triggered mechanism (ETM) with switch-adjustable threshold parameters and dormancy waking functions is designed. This triggering mechanism not only accelerates the convergence of consensus errors in unstable situations, but also prolongs the inter-execution time while maintaining the desired control performance. In the entire control process, only measured input/output data are utilized. Through mathematical analysis, the average consensus errors of closed-loop MASs are proven to converge to zero asymptotically. Finally, the effectiveness and superiority of the proposed method are demonstrated through simulation comparisons.

Keywords: Fully distributed control; Dynamic event-triggered strategy; Model-free adaptive control; Multi-agent systems (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:495:y:2025:i:c:s0096300325000347

DOI: 10.1016/j.amc.2025.129307

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