Force-Position Composite Control Method for Trajectory Accuracy Compensation of Industrial Robots

被引:0
|
作者
Lu Y. [1 ,2 ,3 ]
Guo K. [1 ,2 ,3 ]
Sun J. [1 ,2 ,3 ]
机构
[1] Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, Shandong University, Jinan
[2] Research Center for Aeronautical Component Manufacturing Technology and Equipment, Shandong University, Jinan
[3] School of Mechanical Engineering, Shandong University, Jinan
关键词
compound control; industrial robot; load disturbance; trajectory accuracy;
D O I
10.3901/JME.2022.14.181
中图分类号
学科分类号
摘要
The low joint stiffness of industrial robots and the low machining accuracy under the interference of external load have become the main obstacles to further promotion and application of robots in machining systems. A compound compensation method of force feedforward control and position feedback control is proposed to solve this problem. The force feedforward control part can compensate for the position deviation caused by external load force in advance, and the position feedback part is used to compensate for the position deviation caused by internal factors. A closed-loop control system for online compensation of trajectory error is constructed using a six-dimensional force sensor and a laser tracker. An online compensation experiment is carried out to verify the compensation effect of the proposed method. The errors caused by internal parameters and external environmental factors are considered comprehensively in the method, which improves the tracking accuracy of the robot and can realize the precise control of the robot. The experimental results show that the proposed method is robust and can maintain high trajectory tracking accuracy under large external loads. Under 200 N impact load, the peak error of path trajectory is 0.082 mm, and the stability error is 0.047 mm, which lays a foundation for high precision robot machining under complex working conditions. © 2022 Editorial Office of Chinese Journal of Mechanical Engineering. All rights reserved.
引用
收藏
页码:181 / 189
页数:8
相关论文
共 32 条
  • [1] KIM S H, NAM E, HA T I, Et al., Robotic machining: A review of recent progress[J], International Journal of Precision Engineering and Manufacturing, 20, 9, pp. 1629-1642, (2019)
  • [2] CHEN Yonghua, DONG Fenghua, Robot machining: Recent development and future research issues[J], The International Journal of Advanced Manufacturing Technology, 66, 9, pp. 1489-1497, (2013)
  • [3] ZHANG Yiran, Kai GUO, SUN Jie, Investigation on the milling performance of amputating clamping supports for machining with industrial robot[J], The International Journal of Advanced Manufacturing Technology, 102, 9-12, pp. 3573-3586, (2019)
  • [4] HAO Daxian, WANG Wei, WANG Qilong, Applications and development trend of robotics in composite material process, Journal of Mechanical Engineering, 55, 3, pp. 14-30, (2019)
  • [5] ROTH Z, MOORING B, RAVANI B., An overview of robot calibration[J], IEEE Journal on Robotics and Automation, 3, 5, pp. 377-385, (1987)
  • [6] ZHANG Yiran, Kai GUO, SUN Jie, Et al., Method of postures selection for industrial robot joint stiffness identification[J], IEEE Access, 9, pp. 62583-62592, (2021)
  • [7] PHAM A, AHN H., High precision reducers for industrial robots driving 4th industrial revolution: State of arts,analysis , design , performance evaluation and perspective[J], International Journal of Precision Engineering and Manufacturing-Green Technology, 5, 4, pp. 519-533, (2018)
  • [8] MEGGIOLARO M A, DUBOWSKY S, MAVROIDIS C., Geometric and elastic error calibration of a high accuracy patient positioning system[J], Mechanism and Machine Theory, 40, 4, pp. 415-427, (2005)
  • [9] GONG Chunhe, YUAN Jingxia, NI Jun, Nongeometric error identification and compensation for robotic system by inverse calibration[J], International Journal of Machine Tools & Manufacture, 40, 14, pp. 2119-2137, (2000)
  • [10] Kai GUO, Yongping PAN, ZHENG Dongdong, Et al., Composite learning control of robotic systems:a least squares modulated approach[J], Automatica, 111, pp. 1-13, (2020)