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Observer-Based Fixed-Time Adaptive Fuzzy Consensus DSC for Nonlinear Multiagent Systems.

Wei Wu, Shaocheng Tong

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    This study presents a fixed-time fuzzy consensus control for nonlinear multiagent systems (MASs) with unmeasurable states. The method ensures stability in fixed-time and avoids singularity issues in control design.

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    Area of Science:

    • Control Theory
    • Artificial Intelligence
    • Systems Engineering

    Background:

    • Nonlinear multiagent systems (MASs) often face challenges with unmeasurable states and unknown dynamics.
    • Output-feedback control is crucial for practical implementation in MASs.
    • Achieving consensus (agreement) in fixed-time is a desirable but complex control objective.

    Purpose of the Study:

    • To develop an output-feedback fixed-time fuzzy consensus control scheme for nonlinear MASs.
    • To address challenges posed by unmeasurable states and unknown internal dynamics.
    • To ensure semi-global practical fixed-time stability (SGPFTS) while avoiding control design singularities.

    Main Methods:

    • Utilizing linear state observers to reconstruct unmeasurable states.
    • Employing fuzzy logic systems (FLS) for adaptive identification of unknown system dynamics.
    • Developing a fixed-time adaptive fuzzy consensus control strategy using nonlinear filter and backstepping techniques.
    • Constructing an integral type Lyapunov function for stability analysis.

    Main Results:

    • The proposed control scheme guarantees semi-global practical fixed-time stability (SGPFTS) for the nonlinear MASs.
    • The method effectively reconstructs unmeasurable states and identifies unknown dynamics.
    • Singularity issues inherent in traditional backstepping methods are successfully avoided.
    • The effectiveness is validated through simulations on unmanned surface vehicles (USVs).

    Conclusions:

    • The presented fixed-time fuzzy consensus control is effective for nonlinear MASs with output feedback.
    • The approach offers improved stability guarantees and robust performance in fixed-time.
    • The methodology provides a viable solution for consensus control problems in complex systems like USVs.