Adaptive neural tracking control for upper limb rehabilitation robot with output constraints

作     者：Zibin Zhang Pengbo Cui Aimin An 

作者机构：College of Electrical and Information EngineeringLanzhou University of TechnologyLanzhouGansuChina 

出 版 物：《IET Cyber-Systems and Robotics》 (智能系统与机器人（英文）)

年 卷 期：2023年第5卷第4期

页      面：49-62页

核心收录：

学科分类：080202[工学-机械电子工程] 08[工学] 0804[工学-仪器科学与技术] 0802[工学-机械工程] 

基　　金：National Natural Science Foundation of China,Grant/Award Numbers:61563032,61963025 Science and Technology Program of Gansu Province,Grant/Award Numbers:22CX8GA131,22YF7GA164 

主　　题：adaptive control full-state and output feedback control output constraints upper limb rehabilitation robot 

摘      要：The authors investigate the trajectory tracking control problem of an upper limb reha-bilitation robot system with unknown *** address the system s uncertainties and improve the tracking accuracy of the rehabilitation robot,an adaptive neural full-state feedback control is *** neural network is utilised to approximate the dy-namics that are not fully modelled and adapt to the interaction between the upper limb rehabilitation robot and the *** incorporating a high-gain observer,unmeasurable state information is integrated into the output feedback *** into consider-ation the issue of joint position constraints during the actual rehabilitation training process,an adaptive neural full-state and output feedback control scheme with output constraint is further *** the perspective of safety in human–robot interaction during rehabilitation training,log-type barrier Lyapunov function is introduced in the output constraint controller to ensure that the output remains within the predefined constraint *** stability of the closed-loop system is proved by Lyapunov stability *** effectiveness of the proposed control scheme is validated by applying it to an upper limb rehabilitation robot through simulations.