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Virtual decomposition control of an exoskeleton robot arm

Published online by Cambridge University Press:  15 October 2014

Cristóbal Ochoa Luna*
Affiliation:
Department of Electrical Engineering, École de technologie supérieure, Montreal, Canada. Emails: [email protected], [email protected]
Mohammad Habibur Rahman
Affiliation:
Department of Electrical Engineering, École de technologie supérieure, Montreal, Canada. Emails: [email protected], [email protected] School of Physical & Occupational Therapy, McGill University, Montreal, Quebec, Canada. Email: [email protected]
Maarouf Saad
Affiliation:
Department of Electrical Engineering, École de technologie supérieure, Montreal, Canada. Emails: [email protected], [email protected]
Philippe Archambault
Affiliation:
School of Physical & Occupational Therapy, McGill University, Montreal, Quebec, Canada. Email: [email protected] Center for Interdisciplinary Research in Rehabilitation (CRIR), Montreal, Quebec, Canada
Wen-Hong Zhu
Affiliation:
Space Exploration, Canadian Space Agency, Longueuil, Quebec, Canada. Email: [email protected]
*
*Corresponding author. E-mail: [email protected]

Summary

Exoskeleton robots, which can be worn on human limbs to improve or to rehabilitate their function, are currently of great importance. When these robots are used in rehabilitation, one aspect that must be fulfilled is their capacity to adapt to different patients without significantly varying their performance. This paper describes the application of a relatively new control technique called virtual decomposition control (VDC) to a seven degrees-of-freedom (DOF) exoskeleton robot arm, named ETS-MARSE. The VDC approach mainly involves decomposing complex systems into subsystems, and using the resulting simpler dynamics to conduct control computation, while strictly ensuring global stability and having the subsystem dynamics interactions rigorously managed and maintained by means of virtual power flow. This approach is used to deal with different masses, joint stiffness and biomechanical variations of diverse subjects, allowing the control technique to naturally adapt to the variances involved and to maintain a successful control task. The results obtained in real time on a 7DOF exoskeleton robot arm show the effectiveness of the approach.

Type
Articles
Copyright
Copyright © Cambridge University Press 2014 

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