隨著對醫療復健設備之需求增加以及機器人技術進步，下肢外骨骼復健機器人技術發展逐漸成熟；其不但可以提高復健之品質與有效性，也大幅改善物理治療師在為病患進行下肢復健之體力付出與負擔。有鑑於此，本文研發一具四自由度之下肢外骨骼復健機器人控制系統，此一控制系統可以結合承重系統以及動力跑步機，進行根據受測者所設計之下肢復健訓練軌跡控制。實務上，一般的比例-微分（Proportional-derivative）控制器可以應用於下肢外骨骼復健機器人之關節馬達伺服控制；然而，當使用於不同體重條件下之受測者時，PD控制器無法自動地調整控制參數，以達到理想的下肢復健軌跡追蹤，也不能對於受試者的體重變化產生相對應得適應性變化。為了解決上述問題，本文研發自適應滑動模式控制器來即時追蹤根據受測者所設計之下肢復健訓練軌跡，以降低不同受試者體重條件下控制效能之影響。根據模擬和實驗結果，本文所提出之自適應滑動模式控制器相較於一般之比例-微分控制器，其不但不需要針對不同受試者進行額外的控制調整參數，也具有更好的軌跡追蹤性能。

.With the increasing demands of rehabilitation facilities and the advances of robotic technologies, lower-limb exoskeleton rehabilitation robots have been proposed to improve the quality and effectiveness of rehabilitation, as well as to reduce the effort and load of physiotherapists. In this thesis, a four-degrees-of-freedom lower-limb exoskeleton rehabilitation robot control system was developed to work with a body-weight support system and a power treadmill to perform subject specific locomotor training trajectories. Practically, conventional proportional-derivative（PD）control approach may be applied to the servo control of joint motors; However, it cannot adaptively deal with the subject's weight variations. To overcome this challenge, an adaptive sliding mode control approach was realized to track specific locomotor training trajectories with the considerations of different subjects' weights. According to the simulation and experiment results, the adaptive sliding mode controller represented better trajectory tracking performance than conventional PD controllers. Moreover, the adaptive sliding mode controller is capable of dealing with different subjects' conditions without extra adjusting operational control parameters.

[1] G.P. Incremona, G.D. Felici, A. Ferrara, and E. Bassi, “A Supervisory Sliding Mode Control Approach for Cooperative Robotic System of Systems,” Systems Journal on IEEE, Vol. 9, pp. 263 - 272, 2015.
[2] Q. Wu, X. Wang, F. Du, and Q. Zhu, “Fuzzy Sliding Mode Control of An Upper Limb Exoskeleton for Robot-Assisted Rehabilitation,” IEEE International Symposium. Medical Measurements and Applications. , pp. 451 - 456, May 2015.
[3] Y. Liao, Z. Zhou, and Q. Wang, “BioKEX: A Bionic Knee Exoskeleton with Proxy-Based Sliding Mode Control.” IEEE International Conference on Industrial Technology, pp. 125 - 130, March 2015.
[4] J. Yoon, B. Novandy, C.H. Yoon, and K.J. Park, “A 6-DOF Gait Rehabilitation Robot with Upper and Lower Limb Connections that Allows Walking Velocity Updates on Various Terrains,” IEEE/ASME Trans. Mechatronics., Vol. 15, pp. 201 - 215, 2010.
[5] F. Cao, L. Yuanchun, and S. Jixia, “Adaptive Sliding Mode Impedance Control in Lower Limbs Rehabilitation Robotic,” Chinese Automation Congress, IEEE, pp. 310 - 315, 2013.
[6] 鄧本賢,“Path Planning Analysis of A 6-DOF Serial Manipulator Based on PID and Sliding Mode Controllers,” ，碩士學位論文，國立台灣科技大學，民國103年。
[7] A. Duschau-Wicke, T. Brunsch, L. Lünenburger, and R. Riener, “Adaptive Support for Patient-Cooperative Gait Rehabilitation with the Lokomat,” IEEE International Conference on Intelligent Robots and Systems, pp. 2375 - 2361, 2008.
[8] L. Lunenburg, G. Colombo, R. Riener, and V. Dietz, “Biofeedback in Gait Training with The Robotic orthosis Lokomat,” International Conference of the IEEE on Engineering in Medicine and Biology Society, vol. 2, pp. 4888 - 4891, 2004.
[9] A. Duschau-Wicke, J. Von Zitzewitz, A. Caprez, L. Lünenburger, and R. Riener, “Path Control: A method for Patient-Cooperative Robot-Aided Gait Rehabilitation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 18, pp. 38 - 48, 2010.
[10] 劉佳玲，「適應性動作調整對活動下肢生理負荷之影響-以跑步機與橢圓軌道機為例」，碩士學位論文，朝陽科技大學，民國93年。
[11] 程方，王人成，賈曉紅和王愛明，「減重步行訓練機器人的步態規劃方法」，中國康復醫學雜誌，民國97年。
[12] 張立勳，趙凌燕和胡明茂，「下肢康復訓練機器人的重心軌跡控制研究」，應用科技，民國94年。
[13] C. Kirtley, “CGA Normative Gait Database.” [Online]. Available: http://www.clinicalgaitanalysis.com/data/ (Access date: July 18, 2015)
[14] G.V. Lakhekae, L.M. Waghmare, and P.S. Londhe, “Enhanced Dynamic Fuzzy Sliding Mode Controller for Autonomous Underwater Vehicles,” IEEE, Underwater Technology, pp. 1 - 7, 2015.
[15] M.R. Soltanpour, P.O. Otadolajam, and M.K. Khooban, “Robust Control Strategy for Electrically Driven Robot Manipulators: Adaptive Fuzzy Sliding Mode,” IET, Measurement and Technology, Science, Vol. 9, pp. 322 - 334, 2015.
[16] Y. Liao, Z. Zhou, and Q. Wang, “Neural Feedback Passivity of Unknown Nonlinear Systems via Sliding Mode Technique.” IEEE Transaction on Neural Networks and Learning Systems, Vol. 26, pp. 1560 - 1566, 2015.
[17] L. Gui, Z. Yang, X. Yang, W. Gu, and Y. Zhang, “Design and Control Technique Research of Exoskeleton Suit,” IEEE International Conference on Automation and Logistics, pp. 541 - 546, 2007.
[18] J.J. Slotine and W. Li, Applied nonlinear control. New Jersey: Prentice-Hall, pp. 402 - 406, 1991.
[19] M. Spong and M. Vidyasagar, Robot dynamics and control. New York: John Wiley and Sons, pp. 50 - 52, 1989.
[20] A.C. Huang and M.C. Chien, Adaptive Control of Robot Manipulators: A Unified Regressor-Free Approach. Singapore: World Scientific, pp. 89 - 90, 2010.
[21] S.K. Agrawal, S.K. Banala, K. Mankala, V. Sangwan, J.P. Scholz, V. Krishnamoorthy, and W.L. Hsu, “Exoskeletons for Gait Assistance and Training of the MotorImpaired,” IEEE International Conference on Rehabilitation Robotics, pp.1108 - 1113, 2007.
[22] S.K. Banala, S.K. Agrawal, S.H. Kim, and J.P. Scholz, “Novel Gait Adaptation and Neuromotor Training Results Using an Active Leg Exoskeleton,” IEEE/ASME Transactions on Mechatronics, Vol. 15, Issue. 2, pp. 216 - 225, 2010.
[23] B.W. Stansfield, S.J. Hillman, M.E. Hazlewood, and J.E. Robb, “Regression analysis of gait parameters with speed in normal children walking at self-selected speeds,” Gait Posture, Vol. 23, Issue. 3, pp. 288 - 294, 2006.