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    This study introduces an adaptive interval type-3 fuzzy control for unknown nonlinear networked control systems (NCSs) facing denial-of-service (DoS) attacks. The proposed method ensures robust tracking performance and bounded errors despite system uncertainties and cyberattacks.

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    Area of Science:

    • Control Systems Engineering
    • Fuzzy Logic Systems
    • Cybersecurity in Control

    Background:

    • Networked control systems (NCSs) are susceptible to cyberattacks like denial-of-service (DoS), which disrupt normal operation.
    • Unknown nonaffine nonlinear dynamics in discrete-time NCSs pose significant challenges for robust control design.
    • Interval Type-3 (IT3) fuzzy systems offer enhanced uncertainty handling capabilities compared to traditional fuzzy logic.

    Purpose of the Study:

    • To develop an indirect adaptive interval type-3 (IT3) tracking fuzzy control for unknown nonaffine nonlinear discrete-time NCSs under DoS attacks.
    • To propose a novel two-mode attack compensator for estimating unavailable system outputs during attacks.
    • To ensure robust tracking performance and bounded tracking errors in NCSs despite uncertainties and DoS attacks.

    Main Methods:

    • An IT3 fuzzy model (IT3FM) and an IT3 fuzzy controller (IT3FC) are designed using the same IT3 fuzzy sets to reduce computational complexity.
    • A two-mode attack compensator is integrated to estimate system outputs during DoS attacks.
    • A parameter updating algorithm, guaranteed to converge via Lyapunov theory, is presented for adaptive control.
    • A direct defuzzification method is employed to bypass the iterative Karnik-Mendel approach.

    Main Results:

    • The proposed indirect adaptive IT3 fuzzy control method effectively mitigates the adverse effects of DoS attacks.
    • Theoretical analysis confirms the boundedness of the tracking error, demonstrating robust performance.
    • The use of IT3 fuzzy sets for both the model and controller, along with direct defuzzification, reduces computational complexity.
    • Simulations on three nonlinear NCSs validate the robustness and effectiveness of the proposed control strategy.

    Conclusions:

    • The developed indirect adaptive IT3 fuzzy control provides a robust solution for NCSs facing DoS attacks and unknown nonlinear dynamics.
    • The novel attack compensator and simplified IT3 fuzzy system design enhance practical applicability by reducing computational load.
    • The control method ensures reliable system operation and accurate tracking performance in challenging networked environments.