Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 한창수 | - |
dc.date.accessioned | 2018-03-20T07:52:20Z | - |
dc.date.available | 2018-03-20T07:52:20Z | - |
dc.date.issued | 2016-02 | - |
dc.identifier.citation | International Journal of Control, Automation and Systems, v. 14, No. 1, Page. 291-300 | en_US |
dc.identifier.issn | 1598-6446 | - |
dc.identifier.issn | 2005-4092 | - |
dc.identifier.uri | https://link.springer.com/article/10.1007/s12555-014-0250-x | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/49780 | - |
dc.description.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. | en_US |
dc.description.sponsorship | 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). | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | INST CONTROL ROBOTICS & SYSTEMS | en_US |
dc.subject | Adaptive control | en_US |
dc.subject | human robot interaction | en_US |
dc.subject | passivity based | en_US |
dc.subject | robot control | en_US |
dc.title | Passivity based adaptive control for upper extremity assist exoskeleton | en_US |
dc.type | Article | en_US |
dc.relation.no | 1 | - |
dc.relation.volume | 14 | - |
dc.identifier.doi | 10.1007/s12555-014-0250-x | - |
dc.relation.page | 291-300 | - |
dc.relation.journal | International Journal of Control, Automation and Systems | - |
dc.contributor.googleauthor | Khan, Abdul Manan | - |
dc.contributor.googleauthor | Yun, Deok-won | - |
dc.contributor.googleauthor | Ali, Mian Ashfaq | - |
dc.contributor.googleauthor | Zuhaib, Khalil Muhammad | - |
dc.contributor.googleauthor | Yuan, Chao | - |
dc.contributor.googleauthor | Iqbal, Junaid | - |
dc.contributor.googleauthor | Han, Jungsoo | - |
dc.contributor.googleauthor | Shin, Kyoosik | - |
dc.contributor.googleauthor | Han, Changsoo | - |
dc.relation.code | 2016029084 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | DEPARTMENT OF ROBOT ENGINEERING | - |
dc.identifier.pid | cshan | - |
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