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Event-Triggered Model-Free Adaptive Control for Nonlinear Multiagent Systems Under Jamming Attacks.

Xijuan Wang, Changchun Hua, Yunfei Qiu

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    Summary
    This summary is machine-generated.

    This study introduces a novel adaptive control strategy to ensure nonlinear multiagent systems maintain tracking control despite jamming attacks. The method uses only input-output data, enhancing communication network security.

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    Area of Science:

    • Control Theory
    • Cybersecurity
    • Networked Systems

    Background:

    • Nonlinear multiagent systems face security challenges from jamming attacks disrupting communication.
    • Existing control strategies may not adequately address unreliable networks caused by malicious interference.
    • Stackelberg game theory models the adversarial interaction between multiagent systems and jammers.

    Purpose of the Study:

    • To develop a robust tracking control strategy for nonlinear multiagent systems under jamming attacks.
    • To propose a model-free adaptive control method that enhances system security.
    • To reduce communication overhead using an event-triggered scheme.

    Main Methods:

    • Dynamic linearization of the system using a pseudo-partial derivative method.
    • Development of a model-free security adaptive control strategy.
    • Implementation of a fixed threshold event-triggered scheme for communication efficiency.

    Main Results:

    • Achieved bounded tracking control for multiagent systems in the mathematical expectation sense, even with jamming.
    • Demonstrated the effectiveness of the proposed control strategy through simulation examples.
    • Validated that the method requires only input and output information from the agents.

    Conclusions:

    • The proposed model-free adaptive control strategy effectively secures nonlinear multiagent systems against jamming attacks.
    • The event-triggered scheme successfully reduces communication costs without compromising control performance.
    • The approach offers a practical solution for enhancing the security and reliability of networked control systems.