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A PD Computed Torque Control Method with Online Self-gain Tuning for a 3UPS-PS Parallel Robot

Published online by Cambridge University Press:  20 January 2021

Xiaogang Song ,
Yongjie Zhao Open the ORCID record for Yongjie Zhao [Opens in a new window] ,
Chengwei Chen ,
Liang’an Zhang  and
Xinjian Lu
Xiaogang Song
Affiliation:
Department of Mechatronics Engineering, Shantou University, Shantou City, Guangdong 515063, P. R. China, E-mails: 16xgsong@gmail.com, chengwei0101@outlook.com
Yongjie Zhao*
Affiliation:
Department of Mechatronics Engineering, Shantou University, Shantou City, Guangdong 515063, P. R. China, E-mails: 16xgsong@gmail.com, chengwei0101@outlook.com
Chengwei Chen
Affiliation:
Department of Mechatronics Engineering, Shantou University, Shantou City, Guangdong 515063, P. R. China, E-mails: 16xgsong@gmail.com, chengwei0101@outlook.com
Liang’an Zhang
Affiliation:
School of Mechanical Engineering, Anhui University of Technology, Maanshan 243000, P. R. China, E-mail: robotlab@ahut.edu.cn
Xinjian Lu
Affiliation:
Guangdong Goldenwork Robot Technology Ltd, Foshan City, Guangdong 528226, P. R. China, E-mail: tigerw813@126.com
*
*Corresponding author. E-mail: meyjzhao@stu.edu.cn
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Summary

In this paper, an online self-gain tuning method of a PD computed torque control (CTC) is used for a 3UPS-PS parallel robot. The CTC is applied to the 3UPS-PS parallel robot based on the robot dynamic model which is established via a virtual work principle. The control system of the robot comprises a nonlinear feed-forward loop and a PD control feedback loop. To implement real-time online self-gain tuning, an adjustment method based on the genetic algorithm (GA) is proposed. Compared with the traditional CTC, the simulation results indicate that the control algorithm proposed in this study can not only enhance the anti-interference ability of the system but also improve the trajectory tracking speed and the accuracy of the 3UPS-PS parallel robot.

Keywords

3UPS-PS parallel robotDynamicsComputed torque controlPD controlGenetic algorithm

Information

Type
Article
Information
Robotica , Volume 39 , Issue 9 , September 2021 , pp. 1575 - 1587
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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