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    This study introduces a chain-patterned approach for leader-following consensus (LFC) in multiagent systems. It ensures prescribed time bounds and order, even with increasing system scales.

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    Area of Science:

    • Control Theory
    • Networked Systems
    • Robotics

    Background:

    • Multiagent systems require coordination for complex tasks.
    • Leader-following consensus (LFC) is crucial for decentralized control.
    • Scalability and time-bound performance are key challenges in LFC.

    Purpose of the Study:

    • To propose a novel chain-patterned approach for leader-following consensus (LFC).
    • To achieve LFC with prescribed time bounds and order for multiagent systems.
    • To address challenges of increasing scales and unidirectional information flow.

    Main Methods:

    • Utilizing chain-patterned polynomial encodings to manage scale variations.
    • Embedding time-bound-based generators for guaranteed time and bound adherence.
    • Enforcing order property consistent with unidirectional chain information flow.

    Main Results:

    • Successfully confined the effects of scale variation without prior interaction knowledge.
    • Guaranteed LFC within prescribed time and bounds, avoiding infinite time-varying parameters.
    • Achieved the order property, aligning with chain characteristics.

    Conclusions:

    • The proposed chain-patterned approach effectively enables scalable LFC.
    • It provides guaranteed time-bound performance and order in directed chain networks.
    • Demonstrated validity and superiority over existing methods through comparative examples.