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研究生：	許哲勝
論文名稱：	多重智慧控制器應用於機械手臂定位 Applying Multi-Controller of Intelligent for Robot Manipulator Positioning
指導教授：	陳美勇 Chen, Mei-Yung
學位類別：	碩士 Master
系所名稱：	機電工程學系 Department of Mechatronic Engineering
論文出版年：	2013
畢業學年度：	101
語文別：	中文
論文頁數：	66
中文關鍵詞：	機械手臂、適應控制、模糊類神經網路、Lyapunov function
英文關鍵詞：	Robot manipulator, adaptive control, fuzzy neural network, Lyapunov function
論文種類：	學術論文
相關次數：	點閱：495 下載：43
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本論文的主要目的是設計一個六軸機械手臂，並且實現高精密且高穩定之六軸機械手臂。並且在硬體架構、機械手臂之空間三維座標、機械手臂各關節轉動角度與定位追跡的控制作介紹。在空間座標轉換中，本研究使用了D-H 座標系統來運算，並且求得機械手臂中各軸關節之轉換矩陣，再藉由順向運動學與逆向運動學的理論求得機械手臂之空間三維座標與機械手臂各關節轉動角度之轉換關係，並且再藉由設計控制器完成定位控制與追跡控制。
在控制器設計方面，本論文也設計一個多重人工智慧控制器去控制此六軸機械手臂。在控制的過程中，系統會有外界的干擾與不穩定因素，因此本研究所使用之適應性模糊類神經網路控制器會藉由理想輸出位置與機械手臂實際位置之誤差的回授來調整控制器的內部參數，藉由控制器自行調整其內部參數，則可達到高精密與高穩定度的控制法則。最後也提出李阿普諾函式(Lyapunov function)來證明此控制機械手臂系統之穩定性。

The purpose of this paper is to design a six axis robot manipulator, and achieve a high-precision and high-stable six axis robot manipulator. We introduce four part, about hardware architecture, the coordinate of three axis of the robot manipulator, all the rotate degree of the joint of robot manipulator,and the positioning control. In the paper, we use D-H coordinate method to transform the coordinate of three axis and all the rotate degree of the joint of robot manipulator. Finally, we design the controller to achieve positioning and tracing the robot command.
In the controlling of robot manipulator, we design a hybrid artificial intelligence controller to control the six axis robot manipulator. In the control process, there are lots of disturbance and uncertainty, so we use adaptive fuzzy neural network controller to control the robot manipulator. This controller will update its parameter by the error between the command position and real position of the end of robot manipulator, so we can let the robot manipulator to achieve high-precise and high-stable. Finally, we use Lyapunov function to prove the stability of the robot manipulator system.

摘要 ...................................................................................................................... i
Abstract ............................................................................................................... ii
目錄 .................................................................................................................... iii
圖目錄 ..................................................................................................................1
表目錄 ..................................................................................................................1
第一章 緒論 ........................................................................................................1
1 前言 ...........................................................................................................1
2 文獻回顧 ...................................................................................................2
3 研究動機與目的 .......................................................................................7
4 本論文之貢獻 ...........................................................................................8
5 論文架構 ...................................................................................................8
第二章 理論基礎 ..............................................................................................10
1 D-H 座標系統 ..........................................................................................10
1.1 D-H 座標系統定義 ............................................................................10
2 外加干擾源介紹 .....................................................................................13
2.1 摩擦力 ...............................................................................................14
2.2 死區 ...................................................................................................15
3 模糊類神經網路 .....................................................................................15
3.1 模糊控制 ...........................................................................................16
3.2 類神經網路 .......................................................................................16
3.3 倒傳遞學習法則 ...............................................................................17
3.4 模糊類神經網路 ...............................................................................19
第三章 系統設計與介紹 ..................................................................................22
1 機械手臂設計目標 .................................................................................22
2 機械手臂機構設計 .................................................................................22
3 AI 直流伺服馬達介紹 .............................................................................26
4 AI 直流伺服馬達控制卡 .........................................................................30
5 控制流程設計 .........................................................................................31
第四章 系統規劃與控制器設計 ......................................................................33
1 順向運動學 .............................................................................................33
2 逆向運動學 .............................................................................................36
3 模糊類神經網路控制器(FNNC) ............................................................39
4 適應性模糊類神經網路控制器(DAFNNC) ..........................................40
第五章 實驗結果與討論 ..................................................................................47
1 機械手臂控制實驗介紹與流程 .............................................................47
1.1 逆向運動學架構 ...............................................................................48
1.2 順向運動學架構 ...............................................................................48
1.3 DAFNNC 控制器架構 ......................................................................49
1.4 實驗方式展示 ...................................................................................50
2 機械手臂定位實驗 .................................................................................51
2.1 一維定位實驗 ...................................................................................51
2.2 二維定位實驗 ...................................................................................53
3 機械手臂動態連續定位與扇形追跡實驗 .............................................56
3.1 一維動態連續定位實驗 ...................................................................56
3.2 二維扇形追跡實驗 ...........................................................................58
4 實驗數據分析與結論 .............................................................................61
第六章 結論與未來展望 ..................................................................................63
參考文獻 ............................................................................................................64
                                

[1] J. Liu, Y. Zhang and Z. Li, “Improving the Positioning Accuracy of a Neurosurgical Robot System,” IEEE/ASME, Transactions on Mechatronics, vol. 12, pp. 527-533, Oct. 2007.
[2] L. W. Sun, F. Van Meer, Y. Bailly, C. K. Yeung, “Design and Development of a Da Vinci Surgical System Simulator,” IEEE, International Conferenceon Mechatronics and Automation, pp. 1050-1055, 2007.
[3] X. Yu, J. Xu, S. Liu and K. chen, “A control system of a ping-pong robot arm based on fuzzy method,” Internation Conference on Mechatronics and Automation August 7 – 10, Beijing, China.
[4] R. Marin, P. J. Sanz, P. Nebot and R. Wirz, “A ultimodal Interface to Control a Robot Arm via the Web: A Case Study on Remote Programming,” IEEE Trans. on Industrial Electronics, Vol. 52, No. 6, December 2005
[5] D. E. Whitney, “The mathematics of coordinated control prosthetic arm andmanipulators,” Trans. ASME J. Dyn. Syst., Meas. Control, vol. 94, pp.303-309, 1972.
[6] De Lope, R. Gonzalez - Careaga and T. Zarraonandia, “Inverse kinematics of humanoid robots using artificial neural networks,” in Proc. Int. WorkshopComput. Aided Syst. Theory, pp. 216-218, 2003.
[7] R. Behrens, C. K chler, T. F rster and N. Elkmann, “Kinematics analysis of a 3-DOF joint for a novel hyper-redundant robot arm,” IEEE, International Conference on Robotics and Automation, pp. 3224-3229,2011.
[8] H. F. Fauadi, M. S. Jumali, “Modeling and simulation of programmable universal machine for assembly (PUMA) industrial robot for automotive -related assembly process,” IEEE, International Symposium on Information Technology, vol. 3, pp. 1-5, 2008.
[9] M. Tarokh and M. Kim, “Inverse Kinematics of 7-DOF Robots and Limbs by Decomposition and Approximation,” IEEE, Transactions on Robotics,vol. 94, pp. 591-600, 2007.
[10] G. S. Huang, C. K. Tung, H. C. Lin and S. H. Hsiao, “Inverse Kinematics Analysis Trajectory Planning for a Robot Arm,” 8th Asian Control Conference (ASCC), pp. 965-970, May 2011.
[11] M. O. Efe, “Fractional Fuzzy Adaptive Sliding-Mode Control of a2-DOF Direct-Drive Robot Arm,” IEEE Trans. On Systems, Man, Cybernetics-Part B: Cybernetics, Vol.38, No.6, December 2008
[12] R. J. Wai and Z. W. Yang, “Adaptive Fuzzy Neural Network Control Design via a T-S Fuzzy Model for a Robot Manipulator Including Actuator Dynamics,” IEEE Trans. On Systems, Man, Cybernetics-Part B:
Cybernetics, Vol.38, No.6, December 2008
[13] R. J. Wai and P. C. Chen, “Robust Neural-Fuzzy-Network Control for Robot Manipulator Including Actuator Dynamics,” IEEE Trans. On Induttrial Electronics, Vol.53, No.4, August 2006
[14] P. I. Corke, “A Simple and Systematic Approach to Assigning Denavit –Hartenberg Parameters,” IEEE, Transactions on Robotics, vol.23,pp.590-594, 2007.
[15] H. Zhuang, Z.S. Roth and F. Hamano, “A complete and parametrically continuous kinematic model for robot manipulators,” IEEE, Transactions on Robotics and Automation, vol. 8, pp. 451-463, 1992.
[16] M.F. Robinette, R. Manseur, “Robot-Draw, an Internet-based visualization tool for robotics education,” IEEE, Transactions on Education,vol. 44, pp.29-34, 2001.
[17] A. Bazaei and M. Moallem, “Prestiction Friction Modeling and Position Control in Actuated Rotary Arm,” IEEE Trans. on Instrumentation and Measurement, Vol. 59, No. 1, January 2010.
[18] C. C. Chiang and C. C. Yang, “Robust Adaptive Fuzzy Sliding Mode Control for A Class of Uncertain Nonlinear Systems with Unknown Dead-Zone,” 2006 IEEE International Conference on Fuzzy Systems Sheraton Vancouver Wall Centre Hotel, Vancouver, BC, Canada July 16-21,2006
[19] C. H. Choi and J. Y. Choi, “Construction of neural networks to approximate arbitrary continuous functions of one variable,” Electronics Letters, Vol. 28, pp. 151-153, January 1992.
[20] C. H. Wang, C. S. Cheng, and T. T. Lee, “Dynamical Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN),” IEEE Transactions on Systems, Man, and CyberneticsS—PART B: Cybernetics, VOL. 34, NO. 3,JUNE 2004
[21] 洪維恩編著，「Matlab 7 程式設計」，旗標出版股份有限公司，台北市，2006年
[22] 李宜達編著，「控制系統設計與模擬」，全華科技圖書股份有限公司，台北市，2006年
[23] 張斐章、張麗秋編著，「類神經網路」，臺灣東華書局股份有限公司，台北市，2005年

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