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A 7-DoF Upper Limb Exoskeleton Robot Control Using a New Robust Hybrid Controller

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  • Robot and Applications
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Abstract

This article describes a novel robust hybrid control of a 7-DoF upper limb exoskeleton robot. Insensivity can be taken into consideration as the important feature of sliding mode controllers, which is merely valid in the sliding phase. In order to improve controller performance by eliminating or minimizing the time to reach the sliding phase, a sliding surface design can be designed appropriately. In this study, a new sliding mode controller is designed to achieve high performance, which is robust against external disturbances. PID controllers have been widely used in robotic systems since high trajectory can be one of the most important advantages of this controller. Therefore, by combining a new sliding mode controller and a conventional PID controller, a novel hybrid controller is proposed which has excellent performance. Simulation results demonstrate the effectiveness of the proposed control method.

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References

  1. L. Guangye, W. Ye, and Q. Xie, “PID control for the robotic exoskeleton: application to lower extremity rehabilitation,” Proc. of IEEE Conference on Mechatronics and Automation (ICMA), pp. 2345–2350, Chengdu, China, 2012.

    Google Scholar 

  2. W. Qingcong, X. Wang, F. Du, and X. Zhang, “Design and control of a powered hip exoskeleton for walking assistance,” International Journal of Advanced Robotic Systems, vol. 12, no. 3, 2015.

    Google Scholar 

  3. Y. Wen, and J. Rosen, “Neural PID control of robot manipulators with application to an upper limb exoskeleton,” IEEE Transactions on Cybernetics, vol. 43, no. 2, pp.73-684, 2013.

    Google Scholar 

  4. Y. Wen, J. Rosen, and X. Li, “PID admittance control for an upper limb exoskeleton,” Proc. of IEEE Conference on American Control Conference (ACC), pp. 1124–1129, San Francisco, CA, USA, 2011.

    Google Scholar 

  5. Y. Wen, X. Li, and R. Carmona, “A novel PID tuning method for robot control,” Industrial Robot: An International Journal, vol. 40, no. 6, pp. 574–582, 2013.

    Article  Google Scholar 

  6. T. Yong, J. Zheng, Y. Lin, T. Wang, H. Xiong, G. He, and D. Xu, “Fuzzy PID control method of deburring industrial robots,” Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2447–2455, 2015.

    Article  Google Scholar 

  7. R. Mehran, A. Ghanbari, and M. M. Ettefagh, “Robust adaptive control of a bio-inspired robot manipulator using bat algorithm,” Expert Systems with Applications, vol. 56, pp. 164–176, 2016.

    Article  Google Scholar 

  8. R. Mehran, H. Komijani, A. Ghanbari, and M. M. Ettefagh, “Optimal novel super-twisting PID sliding mode control of a MEMS gyroscope based on multi-objective bat algorithm,” Microsystem Technologies, vol. 24, no. 6, pp. 2835–2846, 2018.

    Article  Google Scholar 

  9. R. Mehran and A. Ghanbari, “Computed torque control of a caterpillar robot manipulator using neural network,” Advanced Engineering Forum, vol. 15, pp. 106–118, 2016.

    Article  Google Scholar 

  10. C. Dongkyoung, “Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates,” IEEE Trans. on Control Systems Technology, vol. 12, no. 4, pp. 637–644, 2004.

    Article  Google Scholar 

  11. Z. Man, A. P. Paplinski, and H. R. Wu, “A robust MIMO terminal sliding mode control scheme for rigid robotic manipulators,” IEEE Trans. on Automatic Control, vol. 39, no. 12, pp. 2464–2469, 1994.

    Article  MathSciNet  MATH  Google Scholar 

  12. Y. J. Min and J. H. Kim, “Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots,” IEEE Trans. on Robotics and Automation, vol. 15, no. 3, pp. 578–587,1999.

    Article  Google Scholar 

  13. B. Brahim, M. Saad, C. O. Luna, P. S. Archambault, and M. H. Rahman, “Sliding mode control of an exoskeleton robot based on time delay estimation,” Proc. of IEEE Conference on Virtual Rehabilitation (ICVR), pp. 1–2, Montreal, QC, Canada, 2017.

    Google Scholar 

  14. W. Xiaofeng, X. Li, J. Wang, X. Fang, and X. Zhu, “Datadriven model-free adaptive sliding mode control for the multi degree-of-freedom robotic exoskeleton,” Information Sciences, vol. 327, pp. 246–257, 2016.

    Article  MathSciNet  MATH  Google Scholar 

  15. R. M. Habibur, M. Saad, J. P. Kenné, and P. S. Archambault, “Nonlinear sliding mode control implementation of an upper limb exoskeleton robot to provide passive rehabilitation therapy,” Proc. of the Conf. on Intelligent Robotics and Applications, pp. 52–62. Springer, Berlin, Heidelberg, 2012.

    Google Scholar 

  16. B. Mahdieh, S. N. Goldar, M. H. Barhaghtalab, and V. Meigoli, “Sliding mode control of an exoskeleton robot for use in upper-limb rehabilitation,” Proc. of IEEE Conference on Robotics and Mechatronics, pp. 694–701, Tehran, Iran, 2015.

    Google Scholar 

  17. A. Ali, M. M. Arefi, F. Sedghi, and V. Abootalebi, “Robust Nonlinear Control Schemes for Finite-Time Tracking Objective of a 5-DOF Robotic Exoskeleton,” International Journal of Control, pp. 1–16, 2018.

    Google Scholar 

  18. C. Jinghui, S. Q. Xie, A. McDaid, and R. Das, “Sliding mode control of an exoskeleton gait rehabilitation robot driven by pneumatic muscle actuators,” Proc. of the 2015.Conf. on ASME International Design Engineering Technical Conferences and Computers and Information in Engineering, pp. V009T07A002-V009T07A002, Boston, Massachusetts, USA, 2015.

    Google Scholar 

  19. R. Amir and R. K. Moghaddam, “Fuzzy sliding mode control of 5 DOF upper-limb exoskeleton robot,” Proc. of IEEE Conference on Technology, Communication and Knowledge, pp. 25–32, Mashhad, Iran, 2015.

    Google Scholar 

  20. O. L. Cristóbal, M. H. Rahman, M. Saad, P. S. Archambault, and S. B. Ferrer, “Admittance-based upper limb robotic active and active-assistive movements,” International Journal of Advanced Robotic Systems, vol. 12, no. 9, 2015.

    Google Scholar 

  21. R. M. Habibur, C. O. Luna, Md. J. Rahman, M. Saad, and P. Archambault, “Force-position control of a robotic exoskeleton to provide upper extremity movement assistance,” International Journal of Modelling, Identification and Control, vol. 21, no. 4, pp. 390–400, 2014.

    Article  Google Scholar 

  22. R. M. Habibur, T. K. Ouimet, M. Saad, J. P. Kenné, and P. S. Archambault, “Development and control of a robotic exoskeleton for shoulder, elbow and forearm movement assistance,” Applied Bionics and Biomechanics, vol. 9, no. 3, pp. 275–292, 2012.

    Article  Google Scholar 

  23. L. C. Ochoa, M. H. Rahman, M. Saad, P. Archambault, and W. H. Zhu, “Virtual decomposition control of an exoskeleton robot arm,” Robotica, vol. 34, no. 7, pp. 1587–1609, 2016.

    Article  Google Scholar 

  24. J. J. Craig, Introduction to Robotics: Mechanics and Control, Pearson/Prentice Hall, Upper Saddle River, NJ, USA, 2005.

    Google Scholar 

  25. R. Mehran, A. Ghanbari, and M. M. Ettefagh, “Hybrid neural network fraction integral terminal sliding mode control of an Inchworm robot manipulator,” Mechanical Systems and Signal Processing, vol. 80, pp. 117–136, 2016.

    Article  Google Scholar 

  26. R. Mehran, A. Ghanbari, and M. M. Ettefagh, “A novel adaptive neural network integral sliding-mode control of a biped robot using bat algorithm,” Journal of Vibration and Control, vol. 24, no. 10, pp. 2045–2060, 2018.

    Article  MathSciNet  Google Scholar 

  27. R. Mehran, “MEMS gyroscope control using a novel compound robust control,” ISA Transactions, vol. 72, pp. 37–43, 2018.

    Article  Google Scholar 

  28. K. K. Dad, W. Jie, and M. C. Lee, “Sensorless reaction force estimation of the end effector of a dual-arm robot manipulator using sliding mode control with a sliding perturbation observer,” International Journal of Control, Automation and Systems, vol. 16, no. 3, pp. 1367–1378, 2018.

    Article  Google Scholar 

  29. J. Seul, “Improvement of tracking control of a sliding mode controller for robot manipulators by a neural network,” International Journal of Control, Automation and Systems, vol. 16, no. 2, pp. 937–943, 2018.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Wisconsin-Milwaukee, 3200 N Cramer Street, Milwaukee, WI, 53211, USA

    Mehran Rahmani

  2. Department of Mechanical/Biomedical Engineering, University of Wisconsin-Milwaukee, 3200 N Cramer Street, Milwaukee, WI, 53211, USA

    Mohammad Habibur Rahman

  3. Department of Electrical and Computer Engineering, College of Engineering, Sultan Qaboos University, Al Khoudh, Muscut, 123, Oman

    Jawhar Ghommam

Authors
  1. Mehran Rahmani
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  2. Mohammad Habibur Rahman
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  3. Jawhar Ghommam
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Corresponding author

Correspondence to Mehran Rahmani.

Additional information

Recommended by Associate Editor Yang Tang under the direction of Editor Hamid Reza Karimi.

Mehran Rahmani received the MSc degree in Mechanical Engineering from University of Tabriz in 2015. He is a Ph.D. candidate in Department of Mechanical Engineering, University of Wisconsin- Milwaukee. His research interests include nonlinear control, adaptive control, fuzzy control, neural network, and robust.

Mohammad Habib Rahman is with the Mechanical and Biomedical Engineering Department, University of Wisconsin-Milwaukee, WI, USA. He received a B.Sc. Engineering (mechanical) degree from Khulna University of Engineering & Technology, Bangladesh in 2001, a Master of Engineering (bio-robotics) degree from Saga University, Japan in 2005 and a Ph.D. degree in Engineering (bio-robotics) from École de technologie supérieure (ETS), Université du Québec, Canada in 2012. He worked as a postdoctoral research fellow in the School of Physical & Occupational Therapy, McGill University (2012-2014). His research interests are in bio-robotics, exoskeleton robot, intelligent system and control, mobile robotics, nonlinear control, control using biological signal such as electromyogram signals.

Jawhar Ghommam is an Associate Professor of control engineering at Sultan Quaboos University in Oman. He is a member of the Control and Energy Management Lab and also an Associate Researcher at the GREPCI-Lab, Ecole de Technologie Superieure, Montreal, QC, Canada. His research interests include nonlinear control of underactuated mechanical systems, adaptive control, guidance and control of autonomous vehicles, and cooperative motion of nonholonomic vehicles.

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Rahmani, M., Rahman, M.H. & Ghommam, J. A 7-DoF Upper Limb Exoskeleton Robot Control Using a New Robust Hybrid Controller. Int. J. Control Autom. Syst. 17, 986–994 (2019). https://doi.org/10.1007/s12555-018-0410-5

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  • DOI: https://doi.org/10.1007/s12555-018-0410-5

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