Neural Control of Robot Manipulators With Trajectory Tracking Constraints and Input Saturation

作者：Yang, Chenguang^*; Huang, Dianye; He, Wei; Cheng, Long

来源：IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(9): 4231-4242.

DOI：10.1109/TNNLS.2020.3017202

• Manipulators
• Lyapunov methods
• Robot kinematics
• Trajectory tracking
• Automation
• Barrier Lyapunov BLF)
• constrained control
• input saturation
• robot manipulator

This article presents a control scheme for the robot manipulator's trajectory tracking task considering output error constraints and control input saturation. We provide an alternative way to remove the feasibility condition that most BLF-based controllers should meet and design a control scheme on the premise that constraint violation possibly happens due to the control input saturation. A bounded barrier Lyapunov function is proposed and adopted to handle the output error constraints. Besides, to suppress the input saturation effect, an auxiliary system is designed and emerged into the control scheme. Moreover, a simplified RBFNN structure is adopted to approximate the lumped uncertainties. Simulation and experimental results demonstrate the effectiveness of the proposed control scheme.

• 单位
  中国科学院研究生院; 北京科技大学