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    This study addresses fast consensus in open multiagent systems (OMASs) with dynamic networks. We developed a control strategy ensuring consensus despite agents joining or leaving, improving convergence rates.

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    Area of Science:

    • Robotics and Control Systems
    • Network Science
    • Distributed Systems

    Background:

    • Open multiagent systems (OMASs) face challenges in achieving consensus due to dynamic network topologies.
    • Random agent entry/exit and network disconnections disrupt system synchronization and slow convergence.

    Purpose of the Study:

    • To investigate the fast consensus problem in OMASs with time-varying network topologies.
    • To develop a robust control strategy that guarantees consensus and optimizes convergence rates.
    • To analyze the impact of agent switching frequency and network dwell time on consensus.

    Main Methods:

    • Derivation of a consensus condition for OMAS with dynamic topology.
    • Establishment of upper bounds for agent switching frequency and network dwell time.
    • Proposal of a convergence rate optimization scheme using the Alternating Direction Method of Multipliers (ADMM).

    Main Results:

    • A novel consensus condition for OMAS with time-varying topology was established.
    • Explicit upper bounds on switching frequency and dwell time were determined to guarantee consensus.
    • The distributed ADMM-based strategy demonstrated superior performance in achieving fast consensus.

    Conclusions:

    • The proposed control strategy effectively ensures fast consensus in OMASs with dynamic network topologies.
    • The findings provide critical insights into managing agent dynamics for reliable system synchronization.
    • The ADMM implementation offers a practical and efficient solution for real-world OMAS applications.