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Command-Filtered Nussbaum Design for Nonlinear Systems with Unknown Control Direction and Input Constraints

Author

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  • Yuxuan Liu

    (School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9IT, UK)

Abstract

This paper studies the problem of adaptive fuzzy control based on command filtering for a class of nonlinear systems characterized by an input dead zone, input saturation, and unknown control direction. First, this paper proposes a novel equivalent transformation technique that simplifies the design complexity of multiple input constraints by converting the input dead zone and saturation nonlinearities into a unified functional form. Subsequently, a fuzzy logic system is utilized to handle the unknown nonlinear functions, and the command-filtering method is employed to address the issue of complexity explosion, while the Nussbaum function is utilized to resolve the challenge of an unknown control direction. Based on Lyapunov stability, it is proven that the tracking error converges to a small neighborhood around the origin, and all closed-loop signals are bounded. Finally, a numerical simulation result and an actual simulation result of a pendulum are presented to verify the feasibility and effectiveness of the proposed control strategy.

Suggested Citation

  • Yuxuan Liu, 2024. "Command-Filtered Nussbaum Design for Nonlinear Systems with Unknown Control Direction and Input Constraints," Mathematics, MDPI, vol. 12(14), pages 1-17, July.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:14:p:2167-:d:1432663
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    References listed on IDEAS

    as
    1. Li, Zheng & Wang, Fang & Zhu, Ruitai, 2021. "Finite-time adaptive neural control of nonlinear systems with unknown output hysteresis," Applied Mathematics and Computation, Elsevier, vol. 403(C).
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