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Passivity based adaptive control for upper extremity assist exoskeleton

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Abstract

Upper limb assist exoskeleton robot requires quantitative techniques to assess human motor function and generate command signal for robots to act in compliance with human motion. To asses human motor function, we present Desired Motion Intention (DMI) estimation algorithm using Muscle Circumference Sensor (MCS) and load cells. Here, MCS measures human elbow joint torque using human arm kinematics, biceps/triceps muscle model and physiological cross sectional area of these muscles whereas load cells play a compensatory role for the torque generated by shoulder muscles as these cells measure desire of shoulder muscles to move the arm and not the internal activity of shoulder muscles. Furthermore, damped least square algorithm is used to estimate Desired Motion Intention (DMI) from these torques. To track this estimated DMI, we have used passivity based adaptive control algorithm. This control techniques is particular useful to adapt modeling error of assist exoskeleton robot for different subjects. Proposed methodology is experimentally evaluated on seven degree of freedom upper limb assist exoskeleton. Results show that DMI is well estimated and tracked for assistance by the proposed control algorithm.

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Author information

Authors and Affiliations

  1. Department of Mechanical Design Engineering, Hanyang University, Seoul, Korea

    Abdul Manan Khan

  2. Department of Mechanical Engineering, Hanyang University, Seoul, Korea

    Deok-won Yun

  3. Department of Mechatornics Engineering, Hanyang University, Sa-3 dong, Ansan, Korea

    Mian Ashfaq Ali, Khalil Muhammad Zuhaib, Chao Yuan & Junaid Iqbal

  4. Department of Mechanical System Engineering, Hansung University, Seoul, Korea

    Jungsoo Han

  5. Department of Robot Engineering, Hanyang University, Sa-3 dong, Ansan, Korea

    Kyoosik Shin & Changsoo Han

Authors
  1. Abdul Manan Khan
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  2. Deok-won Yun
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  3. Mian Ashfaq Ali
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  4. Khalil Muhammad Zuhaib
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  5. Chao Yuan
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  6. Junaid Iqbal
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  7. Jungsoo Han
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  8. Kyoosik Shin
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  9. Changsoo Han
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Corresponding author

Correspondence to Changsoo Han.

Additional information

Recommended by Associate Editor Shinsuk Park under the direction of Editor Euntai Kim. This research was partially supported by the Higher Education Commission of Pakistan by the award letter No. HRDI-UESTPs/Batch-II/South Korea/2012/ and also by the Public welfare & Safety research program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning (No. 2010-0020487) and the Ministry of Trade, Industry and Energy(MOTIE), KOREA, through the Education Support program for Creative and Industrial Convergence (N0000717).

Abdul Manan Khan received his B.Sc. and M.Sc. degrees in Mechatronics&Control Engineering from University of Engineering & Technology, Lahore, Pakistan, in 2007 and 2010, respectively, and his Ph.D. degree in Mechanical Design Engineering from Hanyang University, 2016, Korea. His research interests include rehabilitation and assist exoskeleton robots. He has worked in many projects including lower limb and upper limb assist exoskeleton robots. He is also interested to work on motion planning based differet task executions and control. He also has expertise in Robotic Operating System (ROS) and C++.

Deok-won Yun received the B.S. degree in Mechanical Engineering from Hanyang University in 2004, !and M.S. degree in Mechatronics Engineering from Hanyang University in 2006. He entered Ph.D. degree in Mechanical Engineering at Hanyang University in 2006. He worked in Sindoh from 2008 to 2011 for military service. He is currently pursuing his Ph.D. from the University. His research interests include assistive exoskeleton robots, lower-limb rehabilitation robots, multi-body dynamics and controls.

Mian Ashfaq Ali received his B.Sc. degree in Mechanical Engineering from University of Engineering & Technology, Peshawar, Pakistan in 2006 and an M.S. in Mechanical and a Ph.D. in Mechatronics Engineering from Hanyang University, in 2009 and 2016, respectively. His research interests include vehicle dynamics, cornering performance analysis, and motion control of electric vehicles with In-Wheel Motors.

Khalil Muhammad Zuhaib received the B.E. degree in Electronics Engineering from Quaid-e-Awam University, Pakistan in 2009. He is current enrolled in MS-PhD in Mechatronics Engineering at Hanyang University, Korea. His current research interests include multi-robot motion planning and cooperative control. He is also interested to work on new ideas in this direction.

Yuan Chao received his B.S. degree in mechanical design, Manufacture and Automation Engineering from Harbin Institute of Technology, China in 2010, and his M.S. and Ph.D. degree at the department of Mechatronics Engineering, Hanyang University, Korea. He is currently working at North China Electric Power University as an assistant professor. His research interests includes development of smart sensing system and Robot application in electric power area.

Junaid Iqbal received the B.E. degree in Mechanical Engineering from Quaid-e- Awam University, Pakistan in 2009. He worked for textile and pipe manufacturing industry from 2009 to 2010. Since 2010, he is lecturer in Mechanical Engineering Department, Quaid-e-Awam University College, Larkana, Pakistan. He is currently on study leave and pursuing MS-PhD in Mechatronics Engineering at Hanyang University, Korea. His research interests include advanced vehicle dynamics and control.

Jung-Soo Han received the Ph.D. degree in Biomedical Engineering from the University of Iowa, USA, in 1991. From 1991 to 1992, he was an Assistant Professor and a Chief of the Bioengineering Laboratory of Texas Tech University. From 1992 to 1996, he was an Assistant Professor and a Chief of the Bioengineering Laboratory of West Virginia University. Since 1996, he has been working as a Professor in the Department of Mechanical Systems Engineering at Hansung University, South Korea. His research interests include rehabilitation robots and forceassistive exoskeleton systems.

Kyoosik Shin received the B.S. degree from the Department of Mechanical Engineering, Hanyang University, Seoul, Korea in 1983, and his M.S. and Ph.D. degrees from the Department of Mechanical Engineering, University of Texas at Austin, in 1990 and 1995, respectively. From June 1995 to March 2008, he worked for Samsung SDS as a product development consultant. From March 2008 to August 2009, he was a general manager of Pohang Institute of Intelligent Robotics (PIRO). In September 2009, he joined Hanyang University, Ansan, Gyeonggi-do, Korea as an Associate Professor in the Department of Mechanical Engineering. Currently, he is a Professor in the Department of robot engineering, Hanyang University. His research interests include robot manipulator design, robot design methodology, and energy efficient robot systems.

Changsoo Han received the B.S. degree in Mechanical Engineering from Hanyang University in 1983, and his M.S. and Ph.D. degrees in Mechanical Engineering from University of Texas at Austin in 1985, 1989, respectively. From September 1984 to May 1985, he was a Teaching Assistant with CAD/CAM Lab in the department of engineering of the University of Texas at Austin. From October 1987 to April 1988, he was the consultant for a Lockheed MAC design project for the Lockheed Austin Division. From May 1988 to September 1989, he was a research assistant, Robotics Lab in mechanical engineering manufacturing of the high resolution micro manipulator. He stayed at University of California at Berkeley as a visiting professor from August 1996 to July 1997. In March 1990, he joined Hanyang University, Ansan, Korea as an assistant professor in the department of mechanical engineering. Currently, he is a Professor in the Department of robot engineering, Hanyang University. His research interests include intelligence service robot, high precision robotics and mechatronics, rehabilitation and biomechanics technology using robotics, automation in construction, advanced vehicle control and assistive exoskeleton robots.

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Khan, A.M., Yun, Dw., Ali, M.A. et al. Passivity based adaptive control for upper extremity assist exoskeleton. Int. J. Control Autom. Syst. 14, 291–300 (2016). https://doi.org/10.1007/s12555-014-0250-x

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  • DOI: https://doi.org/10.1007/s12555-014-0250-x

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