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    This study introduces novel adaptive fuzzy controllers for marine vehicle cooperative tracking, enhancing leader following with event-based strategies. These methods ensure precise tracking despite uncertainties and communication limits.

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    Area of Science:

    • Robotics and Control Systems
    • Marine Engineering
    • Artificial Intelligence

    Background:

    • Cooperative tracking control is crucial for coordinated marine vehicle operations.
    • Heterogeneous systems and nonautonomous leaders present significant control challenges.
    • Communication constraints and model uncertainties hinder robust marine vehicle control.

    Purpose of the Study:

    • To develop a fully distributed observer for leader trajectory estimation.
    • To design decentralized adaptive fuzzy event-based controllers for cooperative tracking.
    • To address model uncertainties and communication limitations in marine vehicle systems.

    Main Methods:

    • A fully distributed smooth observer was designed to estimate the leader's trajectory.
    • Three decentralized adaptive fuzzy event-based controllers with fixed, relative, and switching threshold triggering were developed.
    • Lyapunov analysis was used to prove zero-error tracking and absence of Zeno behavior.

    Main Results:

    • The proposed observer effectively estimates the leader's trajectory, reducing input influence.
    • The adaptive fuzzy controllers achieved zero-error tracking for heterogeneous marine vehicles.
    • Event-triggering mechanisms successfully managed communication constraints and model uncertainties.

    Conclusions:

    • The developed observer and controllers provide a robust solution for cooperative tracking of marine vehicles.
    • The fuzzy logic and event-based approaches are effective in handling system complexities.
    • Numerical simulations confirm the practical viability and effectiveness of the proposed control strategies.