Jing Chenghu, Zhang Hui, Liu Yafeng, Zhang Jing
Henan Key Laboratory of Superhard Abrasives and Grinding Equipment, Henan University of Technology, Zhengzhou 450001, China.
School of Mechanical and Electronic Engineering, Henan University of Technology, Zhengzhou 450001, China.
Sensors (Basel). 2024 Apr 26;24(9):2783. doi: 10.3390/s24092783.
The paper investigates a modified adaptive super-twisting sliding mode control (ASTSMC) for robotic manipulators with input saturation. To avoid singular perturbation while increasing the convergence rate, a modified sliding mode surface (SMS) is developed in this method. Using the proposed SMS, an ASTSMC is developed for robot manipulators, which not only achieves strong robustness but also ensures finite-time convergence. The boundary of lumped uncertainties cannot be easily obtained. A modified adaptive law is developed such that the boundaries of time-varying disturbance and its derivative are not required. Considering input saturation in practical cases, an ASTSMC with saturation compensation is proposed to reduce the effect of input saturation on tracking performances of robot manipulators. The finite-time convergence of the proposed scheme is analyzed. Through comparative simulations against two other sliding mode control schemes, the proposed method has been validated to possess strong adaptability, effectively adjusting control gains; simultaneously, it demonstrates robustness against disturbances and uncertainties.
本文研究了一种用于具有输入饱和的机器人机械手的改进型自适应超扭曲滑模控制（ASTSMC）。为了在提高收敛速度的同时避免奇异摄动，该方法中设计了一种改进的滑模面（SMS）。利用所提出的SMS，为机器人机械手开发了一种ASTSMC，它不仅具有很强的鲁棒性，而且能确保有限时间收敛。集总不确定性的边界不易获得。为此开发了一种改进的自适应律，使得不需要时变扰动及其导数的边界。考虑到实际情况中的输入饱和，提出了一种具有饱和补偿的ASTSMC，以减少输入饱和对机器人机械手跟踪性能的影响。分析了所提方案的有限时间收敛性。通过与其他两种滑模控制方案的对比仿真，验证了所提方法具有很强的适应性，能有效调整控制增益；同时，它对干扰和不确定性具有鲁棒性。
