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

delete2025-06-01
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PRE
AI
X
Xiaojie Qiu
W
Wenchao Meng *
王迎春 (Yingchun Wang)
Q
Qinmin Yang
DOI:10.1016/j.amc.2025.129307delete
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Abstract

Abstract

En 中文
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

Journal

Applied Mathematics and Computation cover
Applied Mathematics and Computation
IF:
3.4
Papers:
2.3W
Citations:
3.3W

Organization

N
northeastern university - china
Scholars:
3.1W
Papers: 2.7W
Citations: 37
Z
zhejiang university
Scholars:
17.5W
Papers: 12.0W
Citations: 152