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    Area of Science:

    • Control Theory
    • Systems Engineering
    • Networked Systems

    Background:

    • Multiagent systems (MASs) face challenges from external disturbances and time-varying transmission delays (TDs).
    • Existing control strategies often overlook complex stochastic behaviors and dynamic communication constraints.

    Purpose of the Study:

    • To develop an event-triggered anti-disturbance control strategy for MASs under multiple disturbances and time-varying TDs.
    • To address stochastic behaviors using dual-Markov jumping processes and a novel mapping technique.
    • To reduce communication load via a dynamic event-triggered protocol (DETP) with a packet loss schedule (PLS).

    Main Methods:

    • Utilizing dual-Markov jumping processes and a switching signal to model stochastic behaviors.
    • Designing a DETP incorporating a PLS to optimize communication efficiency.
    • Developing composite anti-disturbance controllers using disturbance observers (DOs).
    • Applying Lyapunov-Krasovskii functional (LKF) and Finsler's lemma for stability analysis.

    Main Results:

    • Derivation of stabilization conditions for the switched dual-Markov jumping MAS (SDMJMAS).
    • Demonstration of reduced communication burden through the DETP.
    • Validation of the proposed control strategy's effectiveness via comparative experiments.

    Conclusions:

    • The proposed event-triggered anti-disturbance control effectively stabilizes MASs with disturbances and delays.
    • The novel approach handles complex stochastic dynamics and optimizes communication.
    • Experimental results confirm the practical applicability and superiority of the developed methods.