Scholarlink

The research team presented the kinematics and dynamics model of the three-wheeled mobile robot in this article. Using these models, control rules are generated to manage model uncertainty, account for wheel slippage, and reduce the impact of external disturbances. This torque model control algorithm is calculated using a neural controller and Backstepping technique. Without knowledge of the kinematic or kinematic parameters of the WMR, the neural controller is used to calculate the torque estimation component for control when only the actual speed of the WMR needs to be known. The Lyapunov criterion is used to check the stability of a closed system. The effectiveness of the controller is verified through simulation using Matlab/Simulink software. In a steady state, the maximum position error of the proposed controller in the x-axis and y-axis are 0.0032 (m) and 0.0018 (m), respectively, and the direction tracking error \(\theta\) is 0.0046 (rad).

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Computational Torque Based on Backstepping Technique Controller and Neural Network Controller for Wheel Mobile Robot

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Than Thi Thuong,
  • Vo Thu Ha,
  • Bùi Huy Hai,
  • Vo Quang Vinh

摘要

The research team presented the kinematics and dynamics model of the three-wheeled mobile robot in this article. Using these models, control rules are generated to manage model uncertainty, account for wheel slippage, and reduce the impact of external disturbances. This torque model control algorithm is calculated using a neural controller and Backstepping technique. Without knowledge of the kinematic or kinematic parameters of the WMR, the neural controller is used to calculate the torque estimation component for control when only the actual speed of the WMR needs to be known. The Lyapunov criterion is used to check the stability of a closed system. The effectiveness of the controller is verified through simulation using Matlab/Simulink software. In a steady state, the maximum position error of the proposed controller in the x-axis and y-axis are 0.0032 (m) and 0.0018 (m), respectively, and the direction tracking error \(\theta\) is 0.0046 (rad).