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Control of an exoskeleton robot arm with sliding mode exponential reaching law

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  • Robotics and Automation
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Abstract

Robots are now working not only in human environments but also interacting with humans, e.g., service robots or assistive robots. A 7DoFs robotic exoskeleton MARSE-7 (motion assistive robotic-exoskeleton for superior extremity) was developed as an assistive robot to provide movement assistance and/or ease daily upper-limb motion. In this paper, we highlight the nonlinear control of MARSE-7 using the modified sliding mode exponential reaching law (mSMERL). Conventional sliding control produces chattering which is undesired for this kind of robotic application as it causes damage to the mechanical structure. Compared to conventional sliding control, our approach significantly reduces chattering and delivers a high dynamic tracking performance. The control architecture was implemented on a field-programmable gate array (FPGA) in conjunction with a RT-PC. In experiments, trajectory tracking that corresponds to typical passive arm movement exercises for single and multi joint movements were performed to evaluate the performance of the developed robot and the controller. Experimental results demonstrate that the MARSE-7 can effectively track the desired trajectories.

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Correspondence to Mohammad H. Rahman.

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Recommended by Editorial Board member Shinsuk Park under the direction of Editor Hyouk Ryeol Choi.

The first author gratefully acknowledges the support provided for this research through a FRQNT-B3 postdoctoral scholarship.

Mohammad H. Rahman is a postdoctoral research fellow with the School of Physical & Occupational Therapy, McGill University, Canada. He received BSc engineering (mechanical) from KUET, Khulna, Bangladesh in 2001, and Master of Engineering (mechanical) from Saga University, Japan in 2005. In 2012, he received a Ph.D. in Electrical Engineering from École de technologie supérieure (ETS), Université du Québec. His research interests are in wearable robot, exoskeleton robot, intelligent system and control, biorobotics, mobile robots, nonlinear control, Artificial Intelligence, Neural Networks, Fuzzy Systems and Control.

Maarouf Saad is a professor in the Department of Electrical Engineering and dean of studies of École de technologie supérieure, Université du Québec, Montreal, Canada. He received a Bachelor and a Master degree in Electrical engineering from Ecole Polytechnique of Montreal respectively in 1982 and 1984. In 1988, he received a Ph.D. from McGill University in Electrical Engineering. He joined École de technologie supérieure in 1987 where he is teaching control theory and robotics courses. His research is mainly in nonlinear control, and optimization applied to robotics and flight control system.

Jean-Pierre Kenné is a professor in the department of Mechanical Engineering and director of the Laboratory of Integrated Production Technologies, École de technologie supérieure (ETS), Université du Québec. He received his master and Ph.D. degrees in Mechanical Engineering from Ecole Polytechnique of Montreal respectively in 1991 and 1998. He has been with GEBO Canada as a project manager in automation in the Digital Control System Department in 1999. He joined ETS in 2000 where he is teaching control theory, fluid power systems, design and control of manufacturing systems courses. His research interests are in capacity planning, control of manufacturing systems and optimization of production systems performances.

Philippe S. Archambault is with the School of Physical & Occupational Therapy, McGill University, Montreal, Canada. He received his BSc in Physics and Occupational Therapy from McGill University. He received an MSc in Biomedical Engineering from University de Montréal, and a Ph.D. in neuroscience, from the same university. His research interests are in motor control, technology in rehabilitation, robotics, wheelchair mobility, and virtual reality. He is teaching neurophysiology and assistive technology.

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Rahman, M.H., Saad, M., Kenné, JP. et al. Control of an exoskeleton robot arm with sliding mode exponential reaching law. Int. J. Control Autom. Syst. 11, 92–104 (2013). https://doi.org/10.1007/s12555-011-0135-1

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