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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
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Prescribed-Time Output Feedback Control for Cyber-Physical Systems Under Output Constraints and Malicious Attacks.

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    Summary
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    This study introduces a novel prescribed-time output feedback control (PTOFC) algorithm for cyber-physical systems (CPSs). It effectively manages output constraints and malicious attacks within a finite time, ensuring system stability and performance.

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    Area of Science:

    • Control Systems Engineering
    • Cyber-Physical Systems Security
    • Nonlinear Control Theory

    Background:

    • Cyber-physical systems (CPSs) face challenges from output constraints and malicious attacks.
    • Existing control methods struggle with output constraints that occur only during finite time intervals (OC-AFT).
    • Traditional control algorithms often have limitations with initial conditions and potential singularities.

    Purpose of the Study:

    • To develop a prescribed-time output feedback control (PTOFC) algorithm for CPSs.
    • To address the complex OC-AFT and malicious attacks in finite time.
    • To create a versatile control strategy applicable to various constraint scenarios, including constraint-free systems.

    Main Methods:

    • A stretch model-based nonlinear mapping function is designed to handle OC-AFT.
    • Fuzzy logic systems are employed to compensate for uncertainties, including attacks and disturbances.
    • A novel practical prescribed-time stability criterion is proposed for the control scheme.

    Main Results:

    • The proposed PTOFC algorithm ensures tracking and observation errors converge to near-zero within a prescribed time.
    • The control scheme effectively accommodates OC-AFT and malicious attacks.
    • Settling time is independent of control parameters and initial states, overcoming limitations of existing methods.

    Conclusions:

    • The developed PTOFC algorithm offers a robust and adaptable solution for CPS control under challenging conditions.
    • The method eliminates issues like excessive initial control inputs and singularity problems.
    • Simulation results validate the effectiveness of the proposed control scheme.