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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
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    Area of Science:

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

    Background:

    • Interval type-2 fuzzy singular systems (SSs) present unique control challenges due to their complexity and inherent uncertainties.
    • External disturbances can significantly degrade the performance and stability of these systems.
    • Existing sampled-data (SD) control methods often exhibit conservatism, limiting their applicability.

    Purpose of the Study:

    • To design a robust memory sampled-data (SD) controller for interval type-2 fuzzy singular systems (SSs).
    • To reduce the conservatism associated with integral terms in stability analysis.
    • To ensure system admissibility and achieve a specified H∞ disturbance attenuation level.

    Main Methods:

    • Development of an improved free-weighting matrix inequality to minimize conservatism.
    • Construction of a novel looped-functional-based Lyapunov-Krasovskii functional (LKF) incorporating sampling interval data.
    • Formulation of new admissibility conditions using linear matrix inequalities (LMIs).

    Main Results:

    • The proposed memory SD controller design guarantees system admissibility for interval type-2 fuzzy SSs.
    • The new approach effectively reduces conservatism in stability analysis.
    • Achieved H∞ disturbance attenuation demonstrates the controller's robustness against external disturbances.

    Conclusions:

    • The developed LMIs-based criteria provide a less conservative and effective method for designing memory SD controllers for fuzzy SSs.
    • Numerical simulations validate the proposed method's usefulness and benefits in practical applications.
    • This work advances the control theory for complex uncertain dynamical systems.