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Composite-Observer-Based Adaptive Consensus Tracking Control for Nonlinear MASs With Unknown Control Directions

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    This study introduces adaptive control for nonlinear multiagent systems (MASs) facing deception attacks. The new strategy ensures followers track the leader

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    Area of Science:

    • Control Theory
    • Systems Engineering
    • Cybersecurity

    Background:

    • Nonlinear multiagent systems (MASs) face challenges in achieving consensus tracking.
    • Unknown control directions and deception attacks complicate control design.

    Purpose of the Study:

    • To develop an adaptive output-feedback consensus tracking control strategy for nonlinear MASs.
    • To address unknown control directions and deception attacks simultaneously.
    • To ensure reliable tracking performance in the presence of adversarial actions.

    Main Methods:

    • A composite observer combining state and disturbance observers was developed.
    • An adaptive attack compensator was proposed to handle unknown gains from attacks.
    • A novel control strategy utilized a logarithmic Lyapunov function and intelligent approximation techniques.

    Main Results:

    • The proposed control strategy ensures boundedness of all closed-loop signals.
    • Synchronous tracking of the leader's output by follower agents was achieved.
    • Effectiveness was validated through two simulation examples.

    Conclusions:

    • The developed composite-observer-based adaptive control is effective for nonlinear MASs under deception attacks.
    • The strategy successfully achieves consensus tracking despite unknown dynamics and adversarial disturbances.
    • This research contributes to robust control design for networked systems facing security threats.