根據國際機器人學會(International Federation of Robotics)的2014年的報告，近年來產業對於工業用機器人需求強勁，工業用機器人出貨量逐年上升，尤其在亞洲製造業國家如大陸台灣。事實上，工資高漲促使廠商以自動化生產取代人力，而工業用機械手臂正在顛覆製造業的生產模式。
　　機械手臂除了機構製造與關鍵零組件的研究發展，機械手臂控制器的發展扮演關鍵核心技術的角色，一個好的控制器設計能使機械手臂穩定到達定位，增進工廠生產效率。本論文首先在MATLAB/Simulink建立機械手臂模型，將粒子群最佳化智慧型演算法應用於最佳化機械手臂PID控制器參數，並與工業中常用的Ziegler-Nichols PID參數調控法比較，最後將模擬結果得出之最佳化PID參數實現於單晶片Arduino DUE 控制IT robot 機械手臂硬體設備。

According to the report in 2014 from International Federation of Robotics, Industries have strong demand on industrial robots. The shipments of industrial robots are soaring annually, especially in Asia countries, for example: Taiwan and China. In fact, the rising wages of workers have urged the companies to upgrade manufacturing to automation. Thus, industrial robots are undergoing a revolution in manufacturing.
Aside from the development of the mechanism manufacturing and key components, however, the robot arm controller plays an important role in the overall performance of the robot system. A suitable controller design can drive the robot arm to the desired position in stable, improving the manufacturing efficiency in the factories. This thesis first models a robot arm in the MATLAB/Simulink for the hardware equipment IT robot arm. The intelligent control method-Particle Swarm Optimization (PSO) is applied to optimize the PID controller parameters. Comparative analysis of the performance of the PSO and Ziegler-Nichols optimizing methods is also presented in this thesis. Finally, Simulation results of the optimal PID parameters were applied on the microcontroller Arduino DUE to control the IT robot hardware.

Abstract………………………………………………………………………………..ii
List of tables…………………………………………………………………………..iv
Figures………………………………………………………………………………...vi
Chapter 1: Introduction………………………………………………………………...1
Chapter 2: Robot Kinematics………………………………………………………....11
Chapter 3: System Architecture………………………………………………………29
Chapter 4: Controllers Design………………………………………………………...35
Chapter 5: Simulation and Experiment Results…………………………..….….…42
Chapter 6: Conclusion……………………………………………………...…..……..57
Appendix A: Hardware Specification………………………………………………...58
Reference………………………………………………………………..……………..68

[1] "Executive Summary World Robotics 2014 Industrial Robot," 2014.
[2] P. Antsaklis, "Defining Intelligent Control," 1993.
[3] V. Santibañez and R. Kelly, "PD control with feedforward compensation for robot manipulators: analysis and experimentation," Robotica, vol. 19, 2001.
[4] A. Tayebi and S. Islam, "Adaptive iterative learning control for robot manipulators: Experimental results," Control Engineering Practice, vol. 14, pp. 843-851, 2006.
[5] V. M. Hernández-Guzmán, V. Santibáñez, and R. Campa, "PID control of robot manipulators equipped with brushless DC motors," Robotica, vol. 27, p. 225, 2008.
[6] J. X. Xiaowen Yu, Shaoli Liu, and Ken Chen, "A control system of a ping-pong robot arm based on fuzzy method," presented at the Proceedings of the 2011 IEEE International Conference on Mechatronics and Automation, 2011.
[7] Z. Bingül and O. Karahan, "A Fuzzy Logic Controller tuned with PSO for 2 DOF robot trajectory control," Expert Systems with Applications, vol. 38, pp. 1017-1031, 2011.
[8] H. M. Fayek, I. Elamvazuthi, N. Perumal, and B. Venkatesh, "A controller based on Optimal Type-2 Fuzzy Logic: systematic design, optimization and real-time implementation," ISA Trans, vol. 53, pp. 1583-91, Sep 2014.
[9] S. B. H. Boubertakh, S. Labiod, "PSO-based PID Control Design for the Stabilization of a Quadrotor," presented at the Proceedings of the 3rd International Conference on Systems and Control, Algiers, Algeria, 2013.
[10] J. F. N. a. D. J. Auxillia, "Adaptive PSO based Tuning of PID Controller for an Automatic Voltage Regulator System," presented at the International Conference on Circuits, Power and Computing Technologies, 2013.
[11] M. W.Spong, Robot Dynamics and Control, WILEY, 1989.
[12] J. J.craig, Introduction to Robotics. Mechanics and Control, 3rd ed.: Pearson Prentice Hall, 2005.
[13] L.-W. Tsai, Robot Analysis: The Mechanics of Serial and Parallel Manipulators: JOHN WILEY & SONS, INC., 1999.
[14] G. C. a. Y. L. Kiam Heong Ang, "PID Control System Analysis, Design,and Technology," IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, vol. 13, pp. 559-576, 2005.
[15] K. Ogata, Discrete-Time Control Systems, 2 ed.: Prentice Hall, 1995.
[16] S. S. Gade, S. B. Shendage, and M. D. Uplane, "On Line Auto Tuning of PID Controller Using Successive Approximation Method," pp. 277-280, 2010.
[17] J. G. Z. a. N. B. Nichols, "Optimum Settings for Automatic Controllers," Trans. ASME, vol. 64, pp. 759-768, 1942.
[18] K. Ogata, Modern Control Engineering 4ed.: Pearson Educational, 2008.
[19] R. C. a. Y. S. Eberhart, "Particle swarm optimization: developments, applications and resources," presented at the Evolutionary Computation, 2001, Seoul, 2001.
[20] Y. S. a. R. Eberhart, "A modified particle swarm optimizer," presented at the IEEE World Congress on Computational Intelligence, 1998.
[21] L. K. Letting, J. L. Munda, and Y. Hamam, "Optimization of a fuzzy logic controller for PV grid inverter control using S-function based PSO," Solar Energy, vol. 86, pp. 1689-1700, 2012.
[22] Terasoft. Inc., IT-Robot Arm User's manual.
[23] Servo City. Available: http://www.servocity.com/
[24] Arduino official website. Available: www.arduino.cc
[25] Microchip, "MCP3204/3208 2.7V 4-Channel/8-Channel 12-Bit A/D Converters with SPI™ Serial Interface," ed.
[26] Sparkfun Electronics. Available: https://www.sparkfun.com/products/12009
[27] Lenovo Thinkpad. Available: www.lenovo.com/