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Prescribed Performance Adaptive Fuzzy Containment Control for Nonlinear Multiagent Systems Using Disturbance

Wei Wang, Hongjing Liang, Yingnan Pan

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    This study presents a new containment control strategy for nonlinear multiagent systems (MASs) facing unknown disturbances and dead-zone outputs. The method ensures follower system outputs converge within the leader system

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    Area of Science:

    • Control Theory
    • Nonlinear Systems
    • Multiagent Systems (MASs)

    Background:

    • Addressing containment control in nonlinear multiagent systems presents challenges due to unknown disturbances and output dead-zones.
    • Existing methods often require prior knowledge of disturbance bounds or struggle with nonlinearities.
    • Ensuring prescribed performance and stability in such complex systems remains a significant research area.

    Purpose of the Study:

    • To develop a robust distributed containment control scheme for nonlinear multiagent systems (MASs).
    • To handle unknown disturbances, nonlinearities, and dead-zone outputs without prior knowledge of disturbance bounds.
    • To achieve prescribed performance, ensuring follower convergence within the convex hull of leaders.

    Main Methods:

    • Utilized fuzzy-logic systems (FLSs) for approximating unknown nonlinear functions within the MASs.
    • Employed a nonlinear disturbance observer to estimate unknown external disturbances.
    • Developed a novel distributed control scheme incorporating adaptive compensation, a Nussbaum function (for unknown control coefficients), and a second-order tracking differentiator (TD) to avoid repeated differentiation.

    Main Results:

    • The proposed control scheme guarantees that the outputs of the follower systems converge to the convex hull defined by the dynamic leaders.
    • All system signals are proven to be semiglobally uniformly ultimately bounded (SGUUB).
    • Local neighborhood containment errors are shown to converge within prescribed performance boundaries.

    Conclusions:

    • The developed distributed containment control strategy effectively addresses complex challenges in nonlinear MASs, including unknown disturbances and dead-zone outputs.
    • The approach ensures system stability and achieves the desired containment performance.
    • Simulation results validate the effectiveness and robustness of the proposed control scheme.