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    Area of Science:

    • Robotics
    • Control Systems Engineering
    • Artificial Intelligence

    Background:

    • Heterogeneous multiagent systems (MASs) present unique challenges in coordinated control.
    • Existing formation control methods often struggle with actuator faults and achieving precise settling times.
    • Distributed control is crucial for scalability and robustness in complex MASs.

    Purpose of the Study:

    • To develop a distributed predefined-time formation control strategy for heterogeneous MASs (UAHs, UGVs, AUVs).
    • To address actuator faults and uncertainties within the control framework.
    • To ensure the formation settling time is independent of initial conditions and control gains.

    Main Methods:

    • Design of a distributed prescribed-time observer for leader state estimation.
    • Construction of an adaptive predefined-time fault-tolerant optimal formation controller.
    • Development of adaptive updating laws for unknown parameters and uncertainties.

    Main Results:

    • Successful estimation of leader states with reduced network flow.
    • Achievement of optimal formation tracking with guaranteed predefined-time convergence.
    • Demonstration of robustness against actuator faults and uncertainties.
    • Settling time is uniformly prescribed, independent of initial conditions and control gains.

    Conclusions:

    • The proposed control strategy effectively achieves distributed predefined-time formation control for heterogeneous MASs.
    • The method offers enhanced robustness and precise timing guarantees, outperforming existing finite/fixed-time approaches.
    • Simulation results validate the efficacy and practical applicability of the developed fault-tolerant control framework.