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dc.contributor.authorLiou, Chun-Daen_US
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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.zh_TW
dc.description.abstractA 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.en_US
dc.description.tableofcontents誌謝 I 中文摘要 II ABSTRACT III 目 錄 IV 圖目錄 VI 表目錄 X 第一章 緒論 1 1.1論文大綱 1 1.2研究動機 1 1.3文獻回顧 4 第二章 動態方程式與阻抗控制法 10 2.1動態方程式之推導 11 2.1.1 Lagrange方程式 11 2.1.2平面撓性關節機械臂動態方程式的推導 12 2.2阻抗控制法 18 2.2.1 阻抗控制法介紹 18 2.2.2阻抗控制法理論推導 21 2.2.3 阻抗參數選取 32 第三章 類神經網路理論 36 3.1 類神經網路簡介 36 3.2神經網路訓練法介紹 40 3.3誤差逆向傳遞學習法 45 3.4類神經式阻抗控制法 51 第四章 模擬結果與討論 58 4.1 機械臂與外在環境接觸力量控制模擬 58 4.1.1系統設定 58 4.1.2平面環境力量控制模擬(外在環境知道的情況) 64 4.1.3非平面環境力量控制模擬 84 4.1.4平面環境力量控制模擬(外在環境未知的情況) 90 第五章 結論與未來展望 103 5.1 結論 103 5.2 未來展望 104 參考文獻 105 附錄 109 連桿動能推導 109zh_TW
dc.subjectFlexible jointen_US
dc.subjectImpedance Controlen_US
dc.subjectNeural Networken_US
dc.titleNeural-Impedance Control for flexible joint robots contact tasksen_US
dc.typeThesis and Dissertationzh_TW
item.openairetypeThesis and Dissertation-
item.fulltextno fulltext-
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