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Performance-Based Distributed Control of Multiagent Systems: A Dual Phase Approach.

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    This study addresses distributed tracking control for uncertain nonlinear systems with unknown time-varying gains. A novel dual-phase approach ensures performance guarantees and robust tracking for networked systems.

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    Area of Science:

    • Control Systems Engineering
    • Networked Systems Theory
    • Nonlinear Dynamics

    Background:

    • Networked systems present challenges due to uncertainty and interconnections.
    • Distributed control requires robust strategies for uncertain parameters and topologies.
    • Strict-feedback systems with unknown gains necessitate advanced adaptive control techniques.

    Purpose of the Study:

    • To develop a distributed tracking control strategy for uncertain nonlinear strict-feedback systems.
    • To handle unknown time-varying gains and directed interaction topologies.
    • To guarantee prescribed performance and robustness in networked systems.

    Main Methods:

    • A dual-phase approach combining robust filtering and adaptive control.
    • Construction of a distributed robust filter for trajectory estimation.
    • Development of an adaptive control protocol using backstepping and a novel Nussbaum function lemma.

    Main Results:

    • The proposed method achieves asymptotic output tracking with prescribed transient response.
    • Unknown control gains, time-varying and state-dependent, are effectively managed.
    • Tracking errors converge to a preassigned residual set with a predefined rate.
    • All internal signals are semi-globally ultimately uniformly bounded (SGUUB).

    Conclusions:

    • The co-designed scheme effectively solves the distributed tracking control problem for complex networked systems.
    • The approach enhances robustness and extends applicability to systems with unknown, time-varying gains.
    • The results demonstrate the effectiveness through illustrative examples.