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    This study introduces an adaptive tracking controller for uncertain nonlinear switched systems using neural networks (NNs) and barrier Lyapunov functions (BLFs). The controller ensures system stability and minimizes tracking errors while respecting output constraints.

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    Area of Science:

    • Control Systems Engineering
    • Nonlinear Dynamics
    • Artificial Intelligence

    Background:

    • Nonlinear switched systems present significant control challenges due to their complex dynamics and inherent uncertainties.
    • Output constraints are common in practical applications, demanding controllers that guarantee performance without violating physical limitations.
    • Traditional backstepping methods can suffer from the 'explosion of complexity' when applied to higher-order systems.

    Purpose of the Study:

    • To develop a novel adaptive approximation-based tracking controller for uncertain nonlinear switched lower-triangular systems with output constraints.
    • To address the 'explosion of complexity' issue inherent in traditional control design techniques.
    • To ensure that all closed-loop system variables remain bounded and the output tracking error is minimized.

    Main Methods:

    • Utilizing neural networks (NNs), specifically radial basis function NNs, to approximate unknown nonlinear functions within the system.
    • Introducing a barrier Lyapunov function (BLF) to transform the constrained system into an unconstrained one, maintaining equivalent control objectives.
    • Employing command filter technique to mitigate the complexity explosion problem associated with recursive backstepping.
    • Extending the approach with an asymmetric BLF to handle asymmetric output constraints.

    Main Results:

    • The designed adaptive controller guarantees ultimate boundedness of all closed-loop variables.
    • The controller effectively ensures that the system output respects the specified constraints.
    • The proposed method achieves arbitrarily small output tracking errors.
    • The generalization to asymmetric output constraints demonstrates the robustness of the approach.

    Conclusions:

    • The developed adaptive tracking controller effectively manages uncertain nonlinear switched systems with output constraints.
    • The combination of BLFs, NNs, and command filters provides a powerful framework for complex control problems.
    • The controller ensures both stability and performance, making it suitable for practical engineering applications.