Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/2426
標題: 類神經式阻抗控制法於撓性關節機械臂力量控制之應用
Neural-Impedance Control for flexible joint robots contact tasks
作者: 劉醇達
Liou, Chun-Da
關鍵字: Flexible joint;撓性關節;Impedance Control;Neural Network;阻抗控制;類神經網路
出版社: 機械工程學系所
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[16]Okuma, S., Ishiguro, A., Furuhashi, T., Uchikawa, Y., 1990, “A Neural Network Compensator for Uncertainties of Robots Manipulators,” Proc. of IEEE Conference on Decision and Control, pp. 3303-3308. [17]Yegerlehner, J.D. and Meckl, P.H., 1992, “Neural Network Control for a Two-Link Manipulator Undergoing Large Payload Changes,” ASME Neural Networks in Manufacturing and Robotics, PED-Vol. 57, pp. 105-116. [18]Lin, S.T. and Tsai, H.C., 1997, “Impedance Control with On-line Neural Network Compensator for Dual-Arm Robots,” Journal of Intelligent & Robotic Systems, Vol. 18, No. 1, pp.87-104. [19]Tsuji, T., Ito, K. and Morasso, P.G., 1996, “Neural Network Learning of Robot Arm Impedance in Operational Space,” IEEE Transactions on System, Man, and Cybernetics-Part B: Cybernetics, Vol. 26, No. 2, pp. 290-298. [20]P. Tomei, 1991, “A simple PD control for robots with elastic joints,” on Autom. Contr., Vol. 36, no. 10, pp. 1208-1213, October 1991. [21]M. G. Forrest-Barlach and S. M. Babcock, “Inverse dynamics position control of a compliant manipulator,” Proc. Of IEEE Int. Conf. on Robotics and Automation, San Francisco, pp. 196-205,1986; IEEE J. of Robotics and Automation, RA-3, pp. 75-83,1987. [22]M. W. Spong and H. Sira-Ramirze, “Robust control of nonlinear sysems,” Proc. of the Ameri. Contr. Conf., Seattle, 1986. [23]M. W. Spong, “Adaptive control of flexible joint manipulators,” Syst. Contr. Lett., Vol. 13, pp. 15-21,1989. [24]F. T. Mrad and S. Ahmad, “Adaptive control of flexible joint robots using position and velocity feedback,” Int. J. Control, Vol. 55, no. 5, pp. 1255-1277, 1992 [25]S. Nicosia and P. Tomei, “A method to design adaptive controllers of flexible joint robots,” Proc. of the 1992 IEEE Int. Conf. on Rob. And Auto., Nice, France, May 1992. [26]G. Ferretti、G. A. Magnani and P. Rocco, “ Impedance control for elastic joints industrial manipulators,” IEEE Transactions on robotics and automation, Vol. 20, No. 3, June 2004 [27]A. C. Huang and M. C. Chien, “Design of a Regressor-free Adaptive Impedance Controller for Flexible-joint Electrically-driven Robots,” IEEE ICIEA, 2009 [28]P. Rocco, On “Stability and control of elastic joint robotic manipulators during constrained-motion tasks ,” IEEE Transactions on robotics and automation, Vol. 13, No. 3, June 1997 [29]R. Ozawa and H. Kobayashi, “A new impedance control concept for elastic joint robots ,” Proc. of the 2003 IEEE Int. Conf. on Rob. And Auto., Taipei, Taiwan, September 14-19. [30]王進德、蕭大全, “類神經網路與模糊控制理論入門,”全華科技圖書股份有限公司, 1994. [31] Kawato, M., Uno, Y., Isobe, M. and Suzuki, R., 1988, “Hierarchical Network Model for Voluntary Movement with Application to Robotics,” IEEE Control Systems Magazine, ”pp. 8-16. [32] Psaltis, D., Sideris, A. and Yamamura, A., 1988, “A Multilayered Neural Network Controller,” IEEE Control Systems Magazine, ” pp. 17-21.
摘要: 
本文所討論的是用一種類神經式阻抗控制法,使撓性關節機械臂和環境接觸的力量控制中,在外在環境之參數未知的情況下,也能達到我們所要求的控制目標。此控制器是一阻抗控制器和線上學習式類神經網路所構成。類神經網路是用來學習在外在環境不確定的情況下,阻抗控制器之參考位置與接觸力的關係。假如阻抗控制器的參考位置輸入對於受控系統的輸出力量存在誤差時,即馬上利用線上學習機構來修正,並且同時調整類神經網路的權值,使控制系統能夠達到我們所要求的控制命令。最後再將以上所討論的各控制設計,以電腦模擬的方式來實現,並驗證與分析模擬結果。

A neural-impedance controller for flexible joint robots contact motion is proposed in this thesis. The objective of this controller is to achieve desired contact force in face of unknown environment . This controller consists of an impedance controller and an online-training neural network. Neural network is used to learn the relation between the contact force and the reference position input in the impedance system with unknown environment. If it consists errors in contact force signal, the online-training mechanism can regulate the weight in the neural network to make the signal fits the force command. Simulation results show that the proposed neural-impedance controller has satisfactory performance.
URI: http://hdl.handle.net/11455/2426
其他識別: U0005-0908201018261800
Appears in Collections:機械工程學系所

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