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Fuzzy Tracking Control for Nonlinear Networked Systems.

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    This study addresses tracking control for uncertain nonlinear networked systems with intermittent data loss. It introduces an interval type-2 fuzzy observer and controller to ensure system stability despite unmeasurable states and parameter variations.

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    Area of Science:

    • Control Systems Engineering
    • Fuzzy Logic Systems
    • Nonlinear System Analysis

    Background:

    • Networked control systems (NCS) face challenges like parameter uncertainties and unmeasurable states.
    • Intermittent measurement loss, a common network-induced constraint, complicates controller design in discrete-time nonlinear NCS.
    • Interval Type-2 (IT2) fuzzy models offer enhanced capability to handle system uncertainties.

    Purpose of the Study:

    • To develop an observer-based tracking control strategy for discrete-time nonlinear NCS with parameter uncertainties.
    • To address the challenge of unmeasurable state variables and intermittent measurement loss.
    • To design a robust control system using IT2 fuzzy logic for improved stability and performance.

    Main Methods:

    • Utilizing an interval type-2 (IT2) fuzzy Takagi-Sugeno model to represent uncertain nonlinear systems.
    • Constructing a premise-variables-independent IT2 fuzzy observer for state estimation.
    • Designing a novel IT2 fuzzy tracking controller incorporating the observer's output.
    • Establishing sufficient criteria for stochastic stability of the closed-loop system.

    Main Results:

    • The proposed IT2 fuzzy observer effectively estimates unmeasurable state variables.
    • The designed IT2 fuzzy tracking controller ensures robust performance under parameter uncertainties and intermittent data loss.
    • Sufficient conditions for the stochastic stability of the closed-loop networked control system are derived.
    • Validation through two illustrative examples demonstrates the practical effectiveness of the proposed methodology.

    Conclusions:

    • The developed observer-based IT2 fuzzy control approach provides a viable solution for tracking control in uncertain discrete-time nonlinear NCS with measurement loss.
    • The IT2 fuzzy framework effectively handles system uncertainties and unmeasurable states, leading to guaranteed stochastic stability.
    • The proposed method offers a robust and effective strategy for networked control system applications facing real-world constraints.