Adaptive patient-cooperative compliant control of lower limb rehabilitation robot

被引:2
|
作者
Chen, Lingling [1 ,2 ]
Huang, Jiabao [1 ]
Wang, Yanglong [1 ]
Guo, Shijie [2 ,3 ]
Wang, Mengge [4 ]
Guo, Xin [1 ,2 ]
机构
[1] Hebei Univ Technol, Sch Artificial Intelligence, Tianjin 300400, Peoples R China
[2] Minist Educ, Intelligent Rehabil Device & Detect Technol Engn R, Tianjin 300400, Peoples R China
[3] Hebei Univ Technol, Sch Mech Engn, Tianjin 300400, Peoples R China
[4] Hebei Univ Technol, Sch Elect Engn, Tianjin 300400, Peoples R China
来源
关键词
Compliant control; Lower limb rehabilitation robot (LLRR); Adaptive admittance controller; Adaptive backstepping controller; Human-robot interaction; DESIGN;
D O I
10.1016/j.birob.2024.100155
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
With the increase in the number of stroke patients, there is a growing demand for rehabilitation training. Robot-assisted training is expected to play a crucial role in meeting this demand. To ensure the safety and comfort of patients during rehabilitation training, it is important to have a patientcooperative compliant control system for rehabilitation robots. In order to enhance the motion compliance of patients during rehabilitation training, a hierarchical adaptive patient-cooperative compliant control strategy that includes patient-passive exercise and patient-cooperative exercise is proposed. A low-level adaptive backstepping position controller is selected to ensure accurate tracking of the desired trajectory. At the high-level, an adaptive admittance controller is employed to plan the desired trajectory based on the interaction force between the patient and the robot. The results of the patient-robot cooperation experiment on a rehabilitation robot show a significant improvement in tracking trajectory, with a decrease of 76.45% in the dimensionless squared jerk (DSJ) and a decrease of 15.38% in the normalized root mean square deviation (NRMSD) when using the adaptive admittance controller. The proposed adaptive patient-cooperative control strategy effectively enhances the compliance of robot movements, thereby ensuring the safety and comfort of patients during rehabilitation training. (c) 2024 The Author(s). Published by Elsevier B.V. on behalf of Shandong University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页数:8
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