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Robust Leaderless Time-Varying Formation Control for Nonlinear Unmanned Aerial Vehicle Swarm System With

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    This study develops a robust control strategy for unmanned aerial vehicle swarms to achieve time-varying formations and trajectory tracking despite disturbances and communication delays. The method ensures swarm stability and accurate formation control.

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    Area of Science:

    • Robotics and Control Systems
    • Aerospace Engineering
    • Swarm Intelligence

    Background:

    • Unmanned Aerial Vehicle Swarm Systems (UAVSSs) require sophisticated control for coordinated maneuvers.
    • Challenges include nonlinear dynamics, external disturbances, and communication delays.
    • Leaderless formations add complexity to decentralized control.

    Purpose of the Study:

    • To address the tracking-oriented robust leaderless time-varying formation (TVF) control problem in UAVSSs.
    • To design a control protocol that ensures formation and trajectory tracking under uncertainties.
    • To provide theoretical guarantees for system stability and performance.

    Main Methods:

    • A novel PD-like formation control protocol incorporating local neighborhood information and differential quantities was designed.
    • The control problem was transformed into analyzing the asymptotic stability of a reduced-order system using matrix decomposition.
    • A theorem was developed to determine unknown control parameters and communication delay bounds.
    • A Lyapunov-Krasovskii functional was employed to verify error convergence.

    Main Results:

    • Sufficient conditions for achieving desired TVF and trajectory tracking were established.
    • The proposed control protocol effectively manages unknown parameters and bounded communication delays.
    • The Lyapunov-Krasovskii functional confirmed asymptotic convergence of flight state errors to zero.
    • Simulation results validated the theoretical findings.

    Conclusions:

    • The developed state-feedback control approach ensures robust and stable time-varying formation control for UAV swarms.
    • The method is effective in handling Lipschitz nonlinear dynamics, external disturbances, and communication delays.
    • This research contributes to the advancement of autonomous swarm coordination and mission execution.