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Adaptive Event-Triggered Sliding-Mode Control for Consensus Tracking of Nonlinear Multiagent Systems With Unknown

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    IEEE Transactions on Cybernetics
    |June 10, 2022
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    Summary

    This study introduces a robust adaptive event-triggered control method for nonlinear multiagent systems (MASs). The approach ensures stable tracking performance while conserving network resources and reducing actuator wear.

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    Area of Science:

    • Control Systems Engineering
    • Robotics
    • Networked Systems

    Background:

    • Leader-following nonlinear multiagent systems (MASs) face challenges with unknown perturbations and limited bandwidth.
    • Existing control methods may not efficiently manage network resources or actuator wear.

    Purpose of the Study:

    • To develop a robust adaptive event-triggered sliding-mode control method for nonlinear MASs.
    • To ensure finite-time state reachability and adaptive tracking performance.
    • To reduce network resource consumption and actuator wear through an adaptive triggering mechanism.

    Main Methods:

    • A distributed integral sliding mode is established for finite-time state reachability.
    • An adaptive triggering control mechanism dynamically adjusts the triggering interval.
    • A distributed event-based robust adaptive sliding-mode protocol is constructed.

    Main Results:

    • The proposed method ensures that the positions and velocities of the MAS converge to the equilibrium point.
    • Sufficient conditions for adaptive tracking performance are derived using Lyapunov stability theory and the Barbalat lemma.
    • Simulations demonstrate the efficacy of the event-based robust adaptive sliding-mode controller.

    Conclusions:

    • The developed control strategy effectively addresses adaptive tracking in nonlinear MASs under uncertainties and bandwidth limitations.
    • The event-triggered approach optimizes resource usage and actuator longevity.
    • The findings offer a robust solution for practical applications of nonlinear MASs.