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    This study introduces a novel consensus algorithm for multiagent systems that uses delayed information to achieve faster synchronization. The algorithm demonstrates robustness and improved convergence speed across various network topologies.

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    Area of Science:

    • Control Theory
    • Networked Systems
    • Robotics

    Background:

    • Multiagent systems require consensus for coordinated behavior.
    • Standard consensus algorithms can be limited by convergence speed.
    • State information delays are common in real-world systems.

    Purpose of the Study:

    • To develop a faster consensus algorithm for linear multiagent systems.
    • To investigate the impact of delayed state information on consensus speed.
    • To ensure stability and robustness of the proposed algorithm.

    Main Methods:

    • Utilizing both current and delayed state information in the consensus protocol.
    • Analyzing system stability using sufficient and necessary conditions.
    • Introducing a coupling strength control parameter for flexible convergence adjustment.
    • Extending analysis to undirected, directed, and switching communication topologies.

    Main Results:

    • The delay-induced consensus algorithm achieves faster synchronization than standard methods under specific conditions.
    • The algorithm is robust to small intrinsic communication or input delays.
    • Stability conditions for the closed-loop system are established.
    • The convergence speed can be flexibly adjusted via a coupling strength parameter.

    Conclusions:

    • Delayed information can accelerate consensus in multiagent systems.
    • The proposed algorithm offers a robust and tunable solution for faster synchronization.
    • The findings are applicable to diverse communication network structures.