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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
    • Robotics
    • Nonlinear Systems Theory

    Background:

    • Complex nonlinear multiagent systems (CNMASs) present significant control challenges.
    • Existing control methods struggle with nonaffine faults and unknown control directions in CNMASs.
    • Finite-time control offers improved performance over traditional asymptotic control.

    Purpose of the Study:

    • To develop a finite-time adaptive control scheme for CNMASs.
    • To address challenges posed by nonaffine faults and partially unknown control directions.
    • To ensure finite-time boundedness of all signals and convergence of cooperative control errors.

    Main Methods:

    • A finite-time command filter is employed to mitigate complexity and chattering issues.
    • An improved error compensation mechanism is utilized to alleviate filter errors.
    • Piecewise Nussbaum functions are incorporated to handle partially unknown control directions.

    Main Results:

    • The proposed cooperative control strategy ensures finite-time boundedness of all closed-loop system signals.
    • Cooperative control errors converge to a predefined upper bound within a finite time.
    • The method demonstrates rapidity and robustness, validated through simulations and a real-world experiment.

    Conclusions:

    • The developed finite-time adaptive control strategy effectively manages CNMASs with nonaffine faults and unknown control directions.
    • The approach guarantees finite-time stability and bounded errors, outperforming existing methods.
    • Experimental validation confirms the practical applicability and effectiveness of the proposed control scheme.