Application of Genetic Algorithm and Taguchi Method to Optimize Parameters of Robot Servo Controller

• Main Authors: HSU, SHAO-HSUAN, 徐紹軒
• Other Authors: Lin ,WEN-TSANN
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/m7sx5r

碩士 === 國立勤益科技大學 === 工業工程與管理系 === 105 === The robotic arm has been used widely in handling, automatic assembly, high repetitive work or some dangerous, difficult works that may not suitable for human in industry. The motion trajectory of the robot arm is a key part of the automatic control. Therefore, the development of precise control technology for robotic arm movement is extremely important. Modifying the controller parameter has been crucial for multi-axis robotic arm with nonlinearly coupled characteristic and not easy to ship position accuracy. There are strong relevant relations between robotic arm precise control and controller parameter design. It would improve the performance of robotic arm with good parameter design; otherwise it will possibly cause its internal mechanism damage with improper parameter design. Therefor it’s necessary to study the servo controller parameter optimization. In this research, we build an optimization model of robotic arm repetitionpositioning accuracy based on real diagnosis research with robotic arm produced by OEM manufacturers. This research seeks the essential factor using the Taguchi method and then improves the simple genetic algorithms to search for the biggest sufficiency parameter for the best servo-control, and improved results for substantive reference on improving the quality of the planning and policy-making reference.