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<p>A fast terminal sliding mode control (FTSM) method based on Fuzzy Wavelet Neural Network (FWNN) is proposed for the stabilization control of wheeled mobile robots under wheel slip conditions. Considering the influence of wheel slip, kinematic and dynamic models of the wheeled robot are established. A novel FTSM controller is designed to achieve rapid convergence of tracking errors within a finite time. To address uncertainties in the wheeled robot’s dynamic model and external disturbances, an FWNN controller is designed to provide real-time compensation using the universal approximation capability of FWNN. A robust neural network-based controller is designed based on H<sub>∞</sub> theory to ensure bounded control signals and system stability. The asymptotic stability of the closed-loop system is proven using Lyapunov theory, and experimental results validate the effectiveness of the proposed algorithm.</p>

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Stabilization control of wheeled mobile robot based on neural sliding mode under wheel slip conditions

  • 期刊论文

  • 发表日期：

    2025年1月16日

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  • Xiaochen Huang,
  • Zhangping You,
  • Wenhui Zhang,
  • Zheng Fang,
  • Dajian Yi,
  • Rui Chen

摘要

A fast terminal sliding mode control (FTSM) method based on Fuzzy Wavelet Neural Network (FWNN) is proposed for the stabilization control of wheeled mobile robots under wheel slip conditions. Considering the influence of wheel slip, kinematic and dynamic models of the wheeled robot are established. A novel FTSM controller is designed to achieve rapid convergence of tracking errors within a finite time. To address uncertainties in the wheeled robot’s dynamic model and external disturbances, an FWNN controller is designed to provide real-time compensation using the universal approximation capability of FWNN. A robust neural network-based controller is designed based on H∞ theory to ensure bounded control signals and system stability. The asymptotic stability of the closed-loop system is proven using Lyapunov theory, and experimental results validate the effectiveness of the proposed algorithm.