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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
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    This study introduces a novel adaptive neural control method using a self-organizing radial basis function neural network (RBFNN) for uncertain nonlinear systems. The direct self-constructing neural controller (DSNC) ensures system stability and accurate tracking performance.

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    Area of Science:

    • Control Engineering
    • Artificial Intelligence
    • Nonlinear Systems

    Background:

    • Nonaffine nonlinear systems present significant control challenges due to uncertainties and ill-defined dynamics.
    • Existing adaptive control methods often struggle with approximating complex nonlinearities effectively.

    Purpose of the Study:

    • To develop an adaptive neural control strategy for uncertain nonaffine nonlinear systems.
    • To design a direct self-constructing neural controller (DSNC) capable of approximating unknown nonlinearities and ensuring system stability.

    Main Methods:

    • Utilized a self-organizing radial basis function neural network (RBFNN) with an adaptive threshold for online controller construction.
    • Developed control and adaptive laws based on Lyapunov stability theory to guarantee closed-loop system stability.
    • Incorporated a robustifying control term to ensure uniform asymptotic convergence of tracking errors.

    Main Results:

    • The proposed DSNC effectively approximates unknown nonlinearities in the system.
    • Lyapunov stability theory confirmed the stability of the closed-loop system.
    • Simulation results demonstrated the effectiveness and superior performance of the proposed adaptive neural control method.

    Conclusions:

    • The self-organizing RBFNN-based DSNC offers a robust solution for adaptive control of uncertain nonaffine nonlinear systems.
    • The method enhances control performance by online adaptation and guarantees system stability.
    • The approach is validated through a practical example, showcasing its effectiveness.