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Event-Based Secure Leader-Following Consensus Control for Multiagent Systems With Multiple Cyber Attacks.

Jinliang Liu, Tingting Yin, Dong Yue

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    This study introduces an event-based control for multiagent systems (MASs) against cyber attacks. It ensures system consensus despite dynamic communication changes and network load, validated by simulations.

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    Area of Science:

    • Control Systems Engineering
    • Cybersecurity
    • Networked Systems

    Background:

    • Multiagent systems (MASs) face vulnerabilities from cyber attacks like replay and denial-of-service (DoS).
    • Existing research often assumes fixed communication topologies, which DoS attacks can disrupt.
    • Event-triggered mechanisms can reduce network bandwidth usage by optimizing data transmission.

    Purpose of the Study:

    • To develop an event-based secure leader-following consensus control protocol for MASs under multiple cyber attacks.
    • To address dynamic communication topologies affected by DoS attacks.
    • To ensure mean-square exponential consensus in MASs despite sophisticated cyber threats.

    Main Methods:

    • A novel model for simultaneous replay and DoS attacks was formulated.
    • An event-triggered mechanism was integrated into the consensus protocol.
    • Lyapunov stability theory was employed to derive consensus conditions.
    • Linear matrix inequalities (LMIs) were used to determine controller gains.

    Main Results:

    • Sufficient conditions for mean-square exponential consensus were established.
    • The event-based controller gain was successfully derived.
    • The proposed control strategy effectively handles dynamic topology changes caused by DoS attacks.
    • Simulations confirmed the theoretical results' effectiveness.

    Conclusions:

    • The developed event-based consensus control protocol enhances MAS security against multiple cyber attacks.
    • The approach effectively manages network bandwidth and adapts to changing communication topologies.
    • This work provides a robust framework for secure consensus in networked multiagent systems.