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    This study introduces a novel data-driven control method for autonomous surface vehicles (ASVs) to achieve flocking behavior without needing prior model knowledge. The approach enables coordinated movement and path following, even with unknown parameters and disturbances.

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    Area of Science:

    • Robotics and Control Systems
    • Marine Engineering
    • Artificial Intelligence

    Background:

    • Cooperative control of autonomous surface vehicles (ASVs) is crucial for complex marine operations.
    • Existing methods often require precise model parameters and full state information, limiting practical application.
    • Challenges include unknown model dynamics, external disturbances, and unmeasured velocities in ASV swarms.

    Purpose of the Study:

    • To develop an output-feedback flocking control strategy for ASVs following a leader.
    • To address unknown model parameters, disturbances, and unmeasured velocities using a data-driven approach.
    • To ensure collision avoidance and connectivity within the ASV swarm.

    Main Methods:

    • Proposed a data-driven adaptive anti-disturbance control method for flocking.
    • Developed a data-driven adaptive extended state observer (ESO) for simultaneous estimation of unknown gains, velocities, and disturbances.
    • Implemented output-feedback control laws for both the leading ASV (path-following) and following ASVs (flocking with artificial potential functions and distributed ESOs).

    Main Results:

    • The proposed method successfully establishes flocking behavior without prior model knowledge.
    • Simultaneous estimation of unknown parameters, velocities, and disturbances was achieved using adaptive ESOs.
    • The control strategy effectively guided the ASV swarm along a parameterized path while maintaining formation and avoiding collisions.

    Conclusions:

    • The data-driven adaptive ESO-based output-feedback control is effective for ASV flocking.
    • The method overcomes limitations of unknown parameters and unmeasured velocities in cooperative ASV systems.
    • This approach offers a robust solution for path-guided flocking control in complex marine environments.