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Adaptive Consensus Control of Nonlinear Multiagent Systems With Unknown Control Directions Under Stochastic

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    Summary
    This summary is machine-generated.

    This study introduces an adaptive protocol for nonlinear multiagent systems, achieving consensus even with unknown parameters and switching communication links. The method ensures reliable network coordination despite dynamic topology changes.

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    Area of Science:

    • Control Theory
    • Networked Systems
    • Nonlinear Dynamics

    Background:

    • Consensus is crucial for coordinated behavior in multiagent systems.
    • Existing methods often assume fixed network topologies and known agent parameters.
    • High-order nonlinear systems present unique challenges for consensus achievement.

    Purpose of the Study:

    • To develop an adaptive consensus protocol for high-order nonlinear multiagent systems.
    • To address scenarios with unknown and unidentical model parameters and control directions.
    • To enable consensus over networks with time-varying and disconnected communication topologies.

    Main Methods:

    • Utilizing Nussbaum-type functions for adaptive control design.
    • Developing a novel protocol robust to unknown system parameters and control directions.
    • Analyzing system behavior under stochastically switching communication topologies.

    Main Results:

    • The proposed adaptive protocol guarantees consensus achievement despite unknown agent parameters and control directions.
    • Consensus is achieved even when the communication topology is not constantly connected.
    • Almost sure consensus is demonstrated under specific conditions for networks with non-zero connectivity probability.

    Conclusions:

    • The developed adaptive protocol effectively solves the consensus problem in complex nonlinear multiagent systems.
    • The approach is particularly valuable for networks with dynamic and unreliable communication links.
    • The findings advance the theory and application of consensus control in networked systems.