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Cooperative Output Regulation for Linear Multiagent Systems via Distributed Fixed-Time Event-Triggered Control.

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    IEEE Transactions on Neural Networks and Learning Systems
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    This study introduces a new fixed-time event-triggered control strategy for linear multiagent systems (MASs). The method ensures cooperative output regulation in a guaranteed, finite time, even with intermittent communication, preventing Zeno behavior.

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    Area of Science:

    • Control Theory
    • Systems Engineering
    • Distributed Systems

    Background:

    • Cooperative output regulation is crucial for coordinated multiagent systems (MASs).
    • Existing event-triggered strategies often lack fixed-time convergence or struggle with intermittent communication.
    • Addressing Zeno behavior (infinite event activations in finite time) is a key challenge.

    Purpose of the Study:

    • To develop a novel distributed event-triggered control protocol for fixed-time cooperative output regulation in linear MASs.
    • To ensure convergence in a time independent of initial conditions.
    • To handle intermittent communication while precluding Zeno behavior.

    Main Methods:

    • A dynamic compensator method is employed to design a fixed-time event-triggered control protocol.
    • The control law and compensator are designed for intermittent communication scenarios.
    • A distributed observer-based output feedback controller is proposed for state-unavailable cases.

    Main Results:

    • The proposed control scheme achieves cooperative output regulation in fixed time.
    • Intermittent communication is effectively managed, and Zeno behavior is avoided.
    • Convergence time is independent of initial states, offering predictable performance.

    Conclusions:

    • The novel fixed-time event-triggered strategy successfully addresses cooperative output regulation in linear MASs.
    • The approach is robust to intermittent communication and guarantees finite-time convergence.
    • The observer-based extension provides a viable solution when system states are not directly measurable.