臺灣博碩士論文加值系統

近年，機械手臂產業日新月異，在實務的應用中，手臂存在參數的變化，外部干擾和摩擦力等因素，很難得知手臂確切的物理參數以及外部加工環境的彈性系數，因此，機械手臂因為外在的干擾以及參數的不確定性，會造成控制器設計的困難。當機械手臂在進行加工時，需要設計力量控制來達到加工目的以及防止機械手臂毀損。
本文主要是針對具冗餘自由度的多軸手臂於接觸環境下進行適應性力量控制設計，我們利用任務空間與關節空間的關係同時引入零空間關係式，推導出冗餘機械手臂之任務空間與零空間的數學模型並進行適應性控制器設計。本文考慮到外部干擾及系統本身的不確定性，我們利用模糊類神經系統進行動態估測來克服其問題，且考慮到冗餘機械手臂與制動器的系統動態重新設計適應性控制器。同時，本文針對加工(接觸)環境使用梯度坡降法來估測外部加工環境的彈性系數，其對應的更新律與穩定分析由利耶普諾夫(Lyapunov) 定理推導得到，進而保證系統穩定。最後，我們藉由Matlab電腦模擬將所提之控制器應用於KUKA LWR4七軸機械手臂進行驗證及分析，以說明所提控制策略的有效性。

In recent years, the industrial robot manipulator has been changed wildly used in manufacture. In practical application, it is hard to know the exactly parameters (or models) of the robot manipulator and stiffness coefficient of exterior processing environment since its changes of parameters, exterior disturbances, and friction. As a result, external disturbances and uncertainty of parameters cause difficulty on designing the controller. When the robot manipulator works during the machining, the force control has to be designed in order to smoothly process and avoid damage.
This thesis considers the problem of controlling a redundant robot manipulator in the task space. We discuss the relation between the task space and joint space, and also introduce the knowledge of null space to derive the dynamic model of task and null space. Considering the model system of redundant robot manipulator that is a highly nonlinear dynamic model, with the interaction interference and uncertainty, we utilize the position and force controller design to overcome these problems by fuzzy neural network. Meanwhile, the stiffness coefficient of the environment is unknown. Therefore, we use the gradient descent method to estimate the stiffness coefficient of environment to achieve the adaptive force control. The stability analysis of the closed-loop system and the corresponding update laws are given by Lyapunov stability theorem. Finally, we employ our proposed control scheme in the redundant robot manipulator KUKA LWR4 with 7 –DOF to illustrate the performance and effectiveness.

Abstract in Chinese i
Abstract in English ii
Contents iii
List of Figures v
Chapter One Introduction 1
1.1 Introduction 1
Chapter Two The Dynamic Model of n-Link Redundant Robot Manipulator 4
2.1 Overview 4
2.2 System Description 4
2.3 Coordinate Definition 5
2.3.1 Task Space and Null Space 7
2.3.2 Dynamic Model of Task Space and Null Space 12
Chapter Three Adaptive Force Control Design of n-Link Redundant Robot Manipulator 18
3.1 Fuzzy Neural Networks 18
3.2 The Relationship of Target Impedance 21
3.3 Adaptive Force and Position Control by Fuzzy Neural Network 22
3.3.1 Adaptive Tracking Control by FNN 22
3.4 Adaptive Force Control 28
Chapter Four Simulation Results for KUKA LWR 33
4.1 Planning Scheme of the Desired Trajectory 34
4.2 Simulation Results 34
Chapter Five Conclusions and Future Researches 60
5.1 Conclusions 60
5.2 Future Researches 61
References 62
Appendix A 67

[1]王瑋辰, 多軸機械手臂自適應力量控制設計, 碩士論文, 國立中興大學機械 工程學系, 2015.
[2]高崎凱, 雙足機器人的設計製作與步態規劃及嵌入式單軸伺服控制器實作,碩士論文國立中興大學機械工程學系, 2007.
[3]梶田秀司 仿人機器人/Humanoid robots. 北京, 2007.
[4]詹宗育, 使用模糊類神經統於機械手臂之適應性阻抗力控制設計, 碩士論文, 國立中興大學機械工程學系, 2016.
[5]莊仁豪, 全向式三輪機器人之動力學模式與適應控制設計, 碩士論文國立中興大學機械工程學系, 2008.
[6]陳星名, 具贅餘自由度庫卡機器人之任務空間適應阻抗控制, 碩士論文國立中興大學機械工程學系, 2015.
[7]M. Cefalo, “Notes on the Kuka LWR4 dynamic model,” http://www.coppwliarobotics.com/contributions/LBR4p_dynamic_model.pdf.
[8]R. Colbaugh, H. Seraji, and K. Glasst, “Direct Adaptive Impedance Control of Manipulators,” Proceeding of the 30th conf. in Decision and Control, Brighton, England, 1991.
[9]P. Corke, Robotics, Vision and Control: Fundamental Algorithms in MATLAB, Springer Verlag, 2013.
[10]F. Flacco, A. D. Luca, and O. Khatib, “Control of Redundant Robots Under Hard Joint Constraints: Saturation in the Null Space,” IEEE Transactions on Robotics, vol. 31, no. 3, 2015.
[11]J. Guerin, O. Gibaru, E. Nyiri, and S. Thiery, “Learning local trajectories for high precision robotic tasks . application to KUKA LBR iiwa Cartesian positioning,” IEEE Conf. on Industrial Electronics Society, Oct 2016.
[12]D. Guo, and K. Li, “Acceleration-Level Obstacle-Avoidance Scheme for Motion Planning of Redundant Robot Manipulators,” IEEE International Conf. on Robotics and Biomimetics, Qingdao, China, 2016.
[13]J. He, M. Luo, L. Xu, J. Zhao, and T. Li, “Adaptive Fuzzy Sliding Mode Controller For End-Effectorb Tracking of Redundant Manipulators,” IEEE Conf. on Robotics and Biomimetics, Zhuhai, China, 2015.
[14]L. ilajpah and B. Nemec, “Kinematic Control Algorithms for On-Line Obstacle Avoidance for Redundant Manipulators,” IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems EPFL, Lausanne, Switzerland, 2002.
[15]L. Jin, S. Li, H. M. La, X. Luo, “Manipulability Optimization of Redundant Manipulators Using Dynamic Neural Networks,” IEEE Transactions on Industrial Electronics, vol. 64 Issue 6. Pages 4710-4720, 2017.
[16]O. Khatib, “A Unified Approach for Motion and Force Control of Robot Manipulators: The Operational Space Formulation,” IEEE Journal of Robotics and Automation, vol. RA-3, no. 1, 1987.
[17]O. Khatib, “Inertial Properties in Robotic Manipulation: An Object-Level Framework,” International Journal of Robotics Research, vol. 14, 1995.
[18]S. Li, Y. Zhang, L. Jin, “Kinematic Control of Redundant Manipulators Using Neural Networks,” IEEE Transactions on Neural Network and Learining Systems, vol. PP, Issue. 99, Pages. 1-12, 2016.
[19]H. Lu, X. Zhou and R. Li, “An Optimization Algorithm for Traj ectory Planning of a 7-Dof Redundant Manipulator,” IEEE Chinese Guidance, Navigation and Control Conf. Nanjing, China, 2016.
[20]A. D. Luca, R. Mattone, “Sensorless Robot Collision Detectio and Hybrid Force/Motion Control,” International conf. on Robotics and Automation, Barcelona, Spain, 2005.
[21]J. L. Meza, V. Santibanez, R. Soto, M. A. Llama“Fuzzy, “Self-Tuning PID Semiglobal Regulator for Robot Manipulators,” IEEE Transactions in Industrial Electronics, vol. 56, no. 6, 2012.
[22]Y. Oh, W. K. Chung, Y. Youm, “Extended Impedance Control of Redundant Manipulators Using Joint Space Decomposition,” International Conference on Robotics and Automation, Albuquerque, New Mexico, 1997.
[23]C. Ott, A. Kugi, and Y. Nakamura, “Resolving the Problem of Non-integrability of Nullspace Velocities for Compliance Control of Redundant Manipulators by using Semi-definite Lyapunov functions,” IEEE International Conf. on Robotics and Automation, Pasadena, CA, USA, 2008.
[24]J. Park, W. Chung, and Y. Youm, “On Dynamical Decoupling of Kinematically Redundant Manipulators,” IEEE/RSJ International Conference on Intelligent Robots and Systems, 1999.
[25]P. K. Patchaikani, L. Behera, G. Prasad, “A Single Network Adaptive Critic-Based Redundancy Resolution Scheme for Robot Manipulators” IEEE Transaction on Industrial Electronic, vol. 59, no. 8, 2012.
[26]H. Sadeghian, L. Villani, M. Keshmiri and B. Siciliano, “Dynamic Multi-Priority Control in Redundant Robotic Systems,” Robotica, vol. 31 2013.
[27]H. Sadeghian, M. Keshmiri, L. Villani and B. Siciliano, “Null-space Impedance Control with Disturbance Observer,” IEEE/RSJ International Conf. on Intelligent Robots and Systems, Vilamoura, Algarve, Portugal, 2012.
[28]H. Sadeghian, L. Villani, M. Keshmiri and B. Siciliano, “Task-Space Control of Robot Manipulators With Null-Space Compliance,” IEEE Transactions on Robotics, vol. 30, no. 2, 2014.
[29]C. Schuetz, J. Pfaff, F. Sygulla, D. Rixen and H. Ulbrich, “Motion Planning for Redundant Manipulators in Uncertain Environments based on Tactile Feedback,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany, 2015.
[30]B. Siciliano, J. Jacques, E. Slotine, “A General Framework for Managing Multiple Tasks in Highly Redundant Robotic Systems,” IEEE Conf. Publication, vol. 2, Pages 1211-1216, 1991.
[31]M.W. Spong, S. Hutchinson, M. Vidyasager, “Robot Modeling and Control,” Wiley, 2016.
[32]C. W. Wampler, “Inverse Kinematic Functions for Redundant Manipulators,” IEEE international Conf. on robotics and Automation, vol. 4, 1987.
[33]Y. Wenbin, Q. Ningning, A. Jialin, SUN Lei, “A Redundant Manipulator Design for Active Space Debris Removal,” The 35th Chinese Control Conf. Chengdu, China, 2016.
[34]J. Yuan, “Composite Adaptive Control of Constrained Robots,” IEEE Transactions on Robots and Automation, vol. 12, no. 4, 1996.
[35]J. Zhang, X. Wei, D. Zhou and Q. Zhang, “Trajectory Planning of a Redundant Space Manipulator Based on Improved Hybrid PSO Algorithm,” IEEE International Conference on Robotics and Biomimetics, Qingdao, China, 2016.
[36]L. Zhang, X. Gao, En Li, “An Adaptive Variable Structure Controller for Robotic Manipulators,” The 6th International Forum on Strategic Technology, vol. 1, Pages. 351-355, 2011.
[37]Z. Zhang, L. Zheng, J. Yu, Y. Li, Z. Yu, “Three Recurrent Neural Networks and Three Numerical Methods for Solving Repetitive Motion Planning Scheme of Redundant Robot Manipulators,” IEEE/ASME Transactions on Mechatronics, vol. 2, Issue. 3, 2017.
[38]S. H. Zhou, Y. Tan, B. Zhao, D. Oetomo, “Trajectory Redundancy Iterative Learning Control,” The 13th International Conference on Control, Automation and Systems, Gwangju, Korea, 2013.