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    This study introduces an event-triggered fuzzy control system to manage disturbances in T-S fuzzy systems. A new condition ensures control performance while minimizing data transmission, reducing communication rates effectively.

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    Area of Science:

    • Control Systems Engineering
    • Fuzzy Logic Systems
    • Optimization Algorithms

    Background:

    • Takagi-Sugeno (T-S) fuzzy systems are susceptible to bounded external disturbances.
    • Traditional fuzzy control schemes may suffer performance degradation under event-triggered frameworks due to limited information availability.

    Purpose of the Study:

    • To design a fuzzy controller and estimate the reachable set for T-S fuzzy systems under bounded disturbances.
    • To develop a novel event-triggering condition for fuzzy control systems that ensures performance despite limited data.
    • To establish a relationship between control performance and communication cost in event-triggered systems.

    Main Methods:

    • Design of a fuzzy controller to bound the closed-loop system's reachable set using an ellipsoid.
    • Minimization of the bounding ellipsoid via two optimization algorithms.
    • Proposal of a reachable-set-dependent event-triggering condition for enhanced fuzzy control.

    Main Results:

    • The proposed event-triggering condition ensures satisfactory control performance even with limited information.
    • Explicit bounding ellipsoids for reachable sets are provided.
    • A trade-off relationship between control performance and communication cost is established.

    Conclusions:

    • The novel event-triggering strategy effectively maintains control performance in T-S fuzzy systems.
    • Communication rates can be reduced without compromising control performance when the reachable set is within safe limits.
    • The proposed methods offer a viable approach for efficient and robust fuzzy control under event-triggered conditions.