Impedance control of a rehabilitation robot for interactive training

Authors:
Wei He;Shuzhi Sam Ge;Yanan Li;Effie Chew;Yee Sien Ng
Affiliations:
Robotics Institute and School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China;Robotics Inst. and Sch. of Comp. Science and Eng., Univ. of Electronic Science and Techn. of China, Chengdu, China, Dept. of Electrical & Comp. Eng., National Univ. of Singapore, Singapore, So ...;Department of Electrical & Computer Engineering, National University of Singapore, Singapore,Social Robotics Lab, Interactive Digital Media Institute, National University of Singapore, Singapo ...;Division of Neurology, National University Hospital, Singapore;Department of Rehabilitation Medicine, Singapore General Hospital, Singapore
Venue:
ICSR'12 Proceedings of the 4th international conference on Social Robotics
Year:
2012

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Abstract

In this paper, neural networks based impedance control is developed for a wearable rehabilitation robot in interactions with humans and the environments. The dynamics of the robot are represented by an n-link rigid robotic manipulator. To deal with the system uncertainties and improve the robustness of the system, the adaptive neural networks are used to approximate the unknown model of the constrained robot. With the proposed control, uniform ultimate boundedness of the closed loop system is achieved based on the Lyapunov method. The states of the system converge to a small neighborhood of zero by properly choosing control gains. Extensive simulations are conducted to verify the proposed control.