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    Summary
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    This study introduces a new control method for nonlinear multiagent systems, enabling leaderless output consensus despite varying system orders and unknown parameters. The approach reduces communication needs, enhancing control system efficiency.

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    Area of Science:

    • Control Theory
    • Nonlinear Systems
    • Multiagent Systems

    Background:

    • Leaderless output consensus is crucial for coordinating nonlinear multiagent systems.
    • Heterogeneous system orders and unmatched unknown parameters pose significant control challenges.
    • Existing methods like adaptive backstepping struggle with switching topologies and system variations.

    Purpose of the Study:

    • To develop a novel distributed adaptive leaderless output consensus control scheme.
    • To address challenges posed by heterogeneous system orders and unmatched unknown parameters.
    • To reduce communication load in nonlinear multiagent systems.

    Main Methods:

    • A novel distributed reference system is proposed for each agent, utilizing only relative outputs from neighbors.
    • A fully distributed, reference system-based adaptive control scheme is designed using output-feedback.
    • The method avoids sharing detailed system states, parameters, or virtual reference states.

    Main Results:

    • The proposed control scheme effectively achieves leaderless output consensus in nonlinear multiagent systems.
    • The approach accommodates heterogeneous system orders and unmatched unknown parameters.
    • A significant reduction in communication burden is demonstrated, potentially replacing traditional networks with sensors.

    Conclusions:

    • The developed control scheme offers a robust solution for leaderless output consensus in complex multiagent systems.
    • The method's reduced communication requirements present a practical advantage for real-world applications.
    • The findings are validated through illustrative examples, confirming the scheme's effectiveness.