<p>This paper focuses on achieving predefined time consensus tracking of nonlinear multi-agent systems(MASs) with parameter estimator and controller triggering. Firstly, a set of event-triggered conditions is established in this work for both the controller and the parameter estimator, enabling simultaneous event-triggered in dual channels. Secondly, a dynamic auxiliary variable is incorporated into the event-triggered mechanism to adjust the triggered threshold. Subsequently, the event-triggered mechanism is integrated with predefined-time stability criteria, ensuring that the system achieves practical predefined-time stability while reducing communication resource consumption. Theoretical analysis ensures the boundedness of all closed-loop signals under the proposed scheme, and each follower can track the leader’s desired trajectory within a predefined time. Finally, The effectiveness of the proposed methodology is verified through simulation results.</p>

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Practical predefined-time consensus tracking for nonlinear multi-agent systems with dynamic event-triggered and parameter estimator triggering

  • Qiang Yang,
  • Qingkun Yu,
  • Libing Wu,
  • Shuyan Qi

摘要

This paper focuses on achieving predefined time consensus tracking of nonlinear multi-agent systems(MASs) with parameter estimator and controller triggering. Firstly, a set of event-triggered conditions is established in this work for both the controller and the parameter estimator, enabling simultaneous event-triggered in dual channels. Secondly, a dynamic auxiliary variable is incorporated into the event-triggered mechanism to adjust the triggered threshold. Subsequently, the event-triggered mechanism is integrated with predefined-time stability criteria, ensuring that the system achieves practical predefined-time stability while reducing communication resource consumption. Theoretical analysis ensures the boundedness of all closed-loop signals under the proposed scheme, and each follower can track the leader’s desired trajectory within a predefined time. Finally, The effectiveness of the proposed methodology is verified through simulation results.