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Event-Triggered Consensus Control for Multi-Agent Systems Against False Data-Injection Attacks.

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    This study addresses security consensus in time-varying multiagent systems (MASs) against false data-injection attacks (FDIAs). An event-triggered control method ensures consensus despite attacks and uncertainties.

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    Area of Science:

    • Control Theory
    • Networked Systems
    • Cybersecurity

    Background:

    • Multiagent systems (MASs) face security challenges from false data-injection attacks (FDIAs) compromising data integrity.
    • Time-varying systems and parameter uncertainties complicate achieving consensus in MASs.
    • Event-triggered control conserves communication resources by updating signals only when necessary.

    Purpose of the Study:

    • To design an event-triggered control strategy for time-varying MASs.
    • To ensure consensus achievement under randomly occurring FDIAs and parameter uncertainties.
    • To maintain H-infinity consensus performance.

    Main Methods:

    • Modeling stealthy FDIAs using Bernoulli processes.
    • Implementing a state-dependent threshold for event-triggered control.
    • Employing stochastic analysis and recursive linear matrix inequalities (LMIs).

    Main Results:

    • Two sufficient criteria derived to guarantee H-infinity consensus performance.
    • Controller gains determined via solving recursive LMIs.
    • Demonstrated effectiveness and applicability through simulation results.

    Conclusions:

    • The proposed event-triggered control method effectively achieves security consensus in MASs.
    • The approach provides robust performance against FDIAs and parameter uncertainties.
    • The method optimizes communication resource utilization.