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Consensus via Time-Varying Feedback for Uncertain Stochastic Nonlinear Multiagent Systems.

Xinglong Niu, Yungang Liu, Fengzhong Li

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    Summary
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    This study achieves consensus in uncertain nonlinear multiagent systems using time-varying feedback. The novel approach compensates for unknown dynamics, enabling reliable leaderless and leader-following consensus.

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    Area of Science:

    • Control Theory
    • Systems Engineering
    • Applied Mathematics

    Background:

    • Multiagent systems often face uncertainties and time-varying parameters.
    • Achieving consensus in such systems is challenging due to unknown control coefficients.

    Purpose of the Study:

    • To develop a time-varying feedback control strategy for uncertain stochastic nonlinear multiagent systems.
    • To achieve almost sure consensus (both leaderless and leader-following) in these complex systems.

    Main Methods:

    • A novel time-varying consensus scheme is proposed.
    • The scheme incorporates a time-dependent function to compensate for system uncertainties and variations.
    • Mathematical protocols are designed to ensure convergence to consensus.

    Main Results:

    • Almost sure leaderless consensus is achieved for the multiagent systems.
    • Almost sure leader-following consensus is also demonstrated.
    • The effectiveness of the proposed method is validated through simulation examples.

    Conclusions:

    • The developed time-varying feedback strategy effectively addresses uncertainties and time-variations in nonlinear multiagent systems.
    • The proposed consensus protocols guarantee almost sure convergence, enhancing system reliability.
    • This research provides a robust framework for consensus achievement in complex dynamic systems.