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    This study addresses leader-following consensus in nonlinear stochastic multi-agent systems (MAS) facing stealthy actuator deception attacks. A novel control algorithm ensures bounded consensus despite attacks and disturbances.

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    Area of Science:

    • Control Theory
    • Systems Engineering
    • Robotics

    Background:

    • Investigates distributed leader-following full-state consensus in nonlinear stochastic multi-agent systems (MAS).
    • Focuses on challenges posed by actuator deception attacks in fixed directed network topologies.
    • Addresses limitations of existing attack models by introducing a novel, stealthier actuator deception attack model.

    Purpose of the Study:

    • To develop a novel distributed output feedback consensus control algorithm for MAS under actuator deception attacks.
    • To overcome the impact of sophisticated, stealthy actuator deception attacks and inherent stochastic disturbances.
    • To ensure leader-following full-state bounded consensus in probability for all agents in the system.

    Main Methods:

    • Introduced a novel actuator deception attack model using a stochastic inverse dynamics system.
    • Designed a distributed linear controller with a compensator for each follower based on relevant outputs.
    • Constructed a new Lyapunov function and employed the exchanging supply function approach for rigorous proof.

    Main Results:

    • Developed a novel distributed output feedback consensus control algorithm effective against stealthy actuator deception attacks.
    • Sufficient conditions for the controller's effectiveness were established.
    • Proved that all agents achieve leader-following full-state bounded consensus in probability.

    Conclusions:

    • The proposed control strategy effectively mitigates the impact of stealthy actuator deception attacks in nonlinear stochastic MAS.
    • The methodology ensures robust leader-following full-state bounded consensus under challenging conditions.
    • Simulation results validate the efficacy of the developed control approach.