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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅立成(Li-Chen Fu) | |
| dc.contributor.author | Li-Yu Chien | en |
| dc.contributor.author | 簡立宇 | zh_TW |
| dc.date.accessioned | 2021-06-17T02:41:27Z | - |
| dc.date.available | 2020-08-24 | |
| dc.date.copyright | 2017-08-24 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-08-16 | |
| dc.identifier.citation | 1. Lugo, R., P. Kung, and C.B. Ma, Shoulder biomechanics. European journal of radiology, 2008. 68(1): p. 16-24.
2. Cirstea, M. and M.F. Levin, Compensatory strategies for reaching in stroke. Brain, 2000. 123(5): p. 940-953. 3. Mozaffarian, D., et al., Executive Summary: Heart Disease and Stroke Statistics--2016 Update: A Report From the American Heart Association. Circulation, 2016. 133(4): p. 447-454. 4. Urwin, M., et al., Estimating the burden of musculoskeletal disorders in the community: the comparative prevalence of symptoms at different anatomical sites, and the relation to social deprivation. Annals of the rheumatic diseases, 1998. 57(11): p. 649-655. 5. Kelley, M.J., P.W. Mcclure, and B.G. Leggin, Frozen shoulder: evidence and a proposed model guiding rehabilitation. journal of orthopaedic & sports physical therapy, 2009. 39(2): p. 135-148. 6. Kwakkel, G., et al., Effects of intensity of rehabilitation after stroke. Stroke, 1997. 28(8): p. 1550-1556. 7. Bütefisch, C., et al., Repetitive training of isolated movements improves the outcome of motor rehabilitation of the centrally paretic hand. Journal of the neurological sciences, 1995. 130(1): p. 59-68. 8. McCabe, J., et al., Comparison of robotics, functional electrical stimulation, and motor learning methods for treatment of persistent upper extremity dysfunction after stroke: a randomized controlled trial. Archives of physical medicine and rehabilitation, 2015. 96(6): p. 981-990. 9. Nef, T., et al. ARMin-Exoskeleton for arm therapy in stroke patients. in Rehabilitation Robotics, 2007. ICORR 2007. IEEE 10th International Conference on. 2007. IEEE. 10. Frisoli, A., et al. Arm rehabilitation with a robotic exoskeleleton in Virtual Reality. in Rehabilitation Robotics, 2007. ICORR 2007. IEEE 10th International Conference on. 2007. IEEE. 11. Wang, S., et al. Active and passive control of an exoskeleton with cable transmission for hand rehabilitation. in Biomedical Engineering and Informatics, 2009. BMEI'09. 2nd International Conference on. 2009. IEEE. 12. Culmer, P.R., et al., A control strategy for upper limb robotic rehabilitation with a dual robot system. IEEE/ASME Transactions on Mechatronics, 2010. 15(4): p. 575-585. 13. Carignan, C.R., M.P. Naylor, and S.N. Roderick. Controlling shoulder impedance in a rehabilitation arm exoskeleton. in Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on. 2008. IEEE. 14. Li, H.-Y., et al. Active control with force sensor and shoulder circumduction implemented on exoskeleton robot NTUH-II. in Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on. 2016. IEEE. 15. Yu, W. and J. Rosen, Neural PID control of robot manipulators with application to an upper limb exoskeleton. IEEE Transactions on cybernetics, 2013. 43(2): p. 673-684. 16. Hamaya, M., et al. Learning assistive strategies from a few user-robot interactions: Model-based reinforcement learning approach. in Robotics and Automation (ICRA), 2016 IEEE International Conference on. 2016. IEEE. 17. Andreasen, D., S. Alien, and D. Backus. Exoskeleton with EMG based active assistance for rehabilitation. in Rehabilitation Robotics, 2005. ICORR 2005. 9th International Conference on. 2005. IEEE. 18. Kiguchi, K. and Y. Hayashi, An EMG-based control for an upper-limb power-assist exoskeleton robot. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2012. 42(4): p. 1064-1071. 19. Gopura, R.A.R.C., K. Kiguchi, and Y. Li. SUEFUL-7: A 7DOF upper-limb exoskeleton robot with muscle-model-oriented EMG-based control. in Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on. 2009. IEEE. 20. Buongiorno, D., et al. A neuromusculoskeletal model of the human upper limb for a myoelectric exoskeleton control using a reduced number of muscles. in World Haptics Conference (WHC), 2015 IEEE. 2015. IEEE. 21. De Luca, A., et al. Collision detection and safe reaction with the DLR-III lightweight manipulator arm. in Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on. 2006. IEEE. 22. Siciliano, B. and O. Khatib, Springer handbook of robotics. 2016: Springer. 23. Spong, M.W. and M. Vidyasagar, Robot dynamics and control. 2008: John Wiley & Sons. 24. Sariyildiz, E. and K. Ohnishi, Stability and robustness of disturbance-observer-based motion control systems. IEEE Transactions on Industrial Electronics, 2015. 62(1): p. 414-422. 25. Sepulchre, R., M. Jankovic, and P.V. Kokotovic, Constructive nonlinear control. 2012: Springer Science & Business Media. 26. Kronander, K. and A. Billard, Passive interaction control with dynamical systems. IEEE Robotics and Automation Letters, 2016. 1(1): p. 106-113. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68907 | - |
| dc.description.abstract | 常見的外骨骼上肢復健機器人的控制方式大致上可以分為兩種方向作探討,以是否有預先設定好的復健軌跡做為區別。 其中以被動療程以及輔助力療程為例,為了能夠幫助病患完成各種復健動作,此兩種療程著重於在預先設定的運動軌跡上,如何有效的幫助、輔助病患同時防止發生任何造成手臂不適的情況。而主動式療程則期望病患能夠隨著自身的動作意圖活動手臂,同時訓練其運動控制能力。
本研究提出一套可應用於外骨骼上肢復健機器人的控制方法。 首先,此方法根據牛頓-歐拉公式建立機台的動態模型。 利用建立好的機台動態模型,我們將可以建立交互作用扭矩觀測器,並且其觀測器僅使用各軸馬達位置以及輸出扭力的資訊,並不需要使用額外的感測器。最後根據此觀測器所測量的數值,本研究提出基於交互作用扭矩觀測器的控制方法,此方法可以作用於被動療程、輔助力療程以及主動療程。 本研究提出的控制方法已經於三位健康受試者之臨床試驗予以驗證,其實驗結果顯示所提出之控制方法在被動療程以及輔助力療程可以提供使用者穩定且安全的復建療程。 並且在主動療程部分,與其他相關的控制方法做比較,本研究所提出的控制方法能夠提升機台在此模式下與使用者互動的順暢度,同時降低使用者的施力。 此基於交互作用扭矩觀測器之外骨骼上肢復健機器人控制方法有潛力在不使用其他額外感測器的情況下,能夠取代一般常見使用力/力矩感測器或者肌電訊號感測器的外骨骼上肢復健機器人控制方法。 | zh_TW |
| dc.description.abstract | The control strategy in the exoskeleton robot arm can be roughly separated into two kinds, with or without predefined trajectory. During passive or active-assistive exercises, the predefined trajectory is needed in order to provide assistant to help the patients complete the tasks. On the other hand, in the active exercises, we expect the patients can freely move their arm to improve their motor control.
In this research, we first build up the dynamic model of the exoskeleton robot arm NTHU-II by Newton-Euler formulation for controlling the nonlinear mechanical structure of the robot. Next, we construct the interactive torque observer based on robot dynamic model and measurements of encoder readings and motor torques. Then, based on the dynamic model and interactive torque, we propose a novel interactive torque observer based control for exoskeleton rehabilitation robot for realizing active, passive, active-assistive mode exercises. Several experiments have been conducted on three subjects which verify the performance of the proposed interactive torque observer based controller. The results show that the proposed control method can manipulate steadily in passive and active-assistive mode exercises. Moreover, the performance in active mode exercises show that it can improve the smoothness and reduce the subject’s effort comparing with the related work. Besides, this method has potential to get rid of additional sensors while preserving the advantages of using sEMG and F/T sensors. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T02:41:27Z (GMT). No. of bitstreams: 1 ntu-106-R04921062-1.pdf: 5350934 bytes, checksum: 44899ddd1a0018d6138c534a1b72920f (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vi LIST OF TABLES vii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Literature Survey 3 1.3 Contribution 5 1.4 Thesis Organization 6 Chapter 2 Preliminary 8 2.1 Upper Limb Rehabilitation Robot NTUH-II 8 2.2 Forward Kinematics 13 2.3 Jacobians 16 2.3.1 Linear Velocity 17 2.3.2 Angular Velocity 17 2.3.3 Application to NTUH-II 18 2.4 Robot Dynamics 19 2.4.1 The Euler-Lagrange equation 19 2.4.2 Newton-Euler Formulation 20 Chapter 3 Design of Control System 27 3.1 Interactive Torque Observer 27 3.2 Control Strategy 30 3.2.1 Passive Mode 31 3.2.2 Active-Assistive Mode 32 3.2.3 Active Mode 33 Chapter 4 Experiment Result 40 4.1 Experiment Protocol 40 4.2 Experiment Result 44 4.2.1 Performance for Passive Mode Exercises 44 4.2.2 Performance for Active-assistive Mode Exercises 48 4.2.3 Performance for Active Mode Exercises 53 Chapter 5 Conclusion 62 REFERENCE 65 Appendix A 67 Appendix B 68 Appendix C 70 | |
| dc.language.iso | en | |
| dc.subject | 運動功能障礙 | zh_TW |
| dc.subject | NTUH-II | zh_TW |
| dc.subject | 被動控制 | zh_TW |
| dc.subject | 輔助力控制 | zh_TW |
| dc.subject | 輔助式療程 | zh_TW |
| dc.subject | 被動式療程 | zh_TW |
| dc.subject | 主動式療程 | zh_TW |
| dc.subject | 復健機械手臂 | zh_TW |
| dc.subject | 主動控制 | zh_TW |
| dc.subject | 上肢復健 | zh_TW |
| dc.subject | active exercise | en |
| dc.subject | active-assistive exercise | en |
| dc.subject | active control | en |
| dc.subject | passive control | en |
| dc.subject | active-assistive control | en |
| dc.subject | NTUH-II | en |
| dc.subject | rehabilitation robotics | en |
| dc.subject | passive exercise | en |
| dc.title | 應用交互作用扭矩觀測器於外骨骼上肢復健機器人之控制 | zh_TW |
| dc.title | Interactive Torque Observer based Exoskeleton Robot Control for Upper Limb Rehabilitation | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 賴金鑫(Jin-Shin Lai),陳文翔(Wen-Shiang Chen),顏炳郎(Ping-Lang Yen),陸哲駒(Jer-Junn Luh) | |
| dc.subject.keyword | 復健機械手臂,主動式療程,被動式療程,輔助式療程,主動控制,被動控制,輔助力控制,上肢復健,運動功能障礙,NTUH-II, | zh_TW |
| dc.subject.keyword | rehabilitation robotics,active exercise,passive exercise,active-assistive exercise,active control,passive control,active-assistive control,NTUH-II, | en |
| dc.relation.page | 84 | |
| dc.identifier.doi | 10.6342/NTU201703498 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-08-16 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位: | 電機工程學系 | |
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| ntu-106-1.pdf 未授權公開取用 | 5.23 MB | Adobe PDF |
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