Impedance Control of Series Elastic Actuators in Exoskeleton Using Recurrent Neural Network

被引：0
|
作者：
Zhang, Qichen [1 ]
Zhu, Aibin [1 ]
Wu, Yuexuan [1 ]
Zhu, Pengcheng [2 ]
Zhang, Xiaodong [1 ]
Cao, Guangzhong [3 ]
机构：
[1] Xi An Jiao Tong Univ, Inst Robot & Intelligent Syst, Shaanxi Key Lab Intelligent Robots, Xian 710049, Shaanxi, Peoples R China
[2] Educ Minist Modern Design & Rotor Bearing Syst, Key Lab, Shaanxi Key Lab Intelligent Robots, Guangzhong, Peoples R China
[3] Shenzhen Univ, Shenzhen Key Lab Electromagnet Control, Shenzhen 518060, Peoples R China
来源：
2019 16TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS (UR) | 2019年
基金：
中国国家自然科学基金;
关键词：
Impedance control; Series Elastic Actuators; Exoskeleton Robot; Recurrent Neural Network;
D O I：
10.1109/urai.2019.8768624
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Exoskeleton robot is a system with human-machine interaction and could help human to carry heavy load. Series elastic actuators (SEAs) in force-controlled robots can achieve compliant interactions with humans. In order to get flexible position and force control, this paper introduced impedance control into exoskeleton robot and use a recurrent neural network to improve the adaptive ability of the system. Finally, simulation results of force tracking and trajectory tracking are presented. By setting virtual impedance parameters, this controller can achieve stable track tracking and force tracking. Recurrent neural network can improve the performance of adaptability and robustness.
引用
收藏
页码：183 / 188
页数：6
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