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Robot Zero-Moment Control Algorithm Based on Parameter Identification of Low-Speed Dynamic Balance

Saixuan Chen1, Jie Yang1,*, Guohua Cui1, Fuzhou Niu2, Baiqiang Yao1, Yu Zhang1
1 Shanghai University of Engineering Science, Shanghai, 201620, China
2 Suzhou University of Science and Technology, Suzhou, 215009, China
* Corresponding Author: Jie Yang. Email:
(This article belongs to this Special Issue: Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)

Computer Modeling in Engineering & Sciences 2023, 134(3), 2021-2039. https://doi.org/10.32604/cmes.2022.022669

Received 21 March 2022; Accepted 13 May 2022; Issue published 20 September 2022

Abstract

This paper proposes a zero-moment control torque compensation technique. After compensating the gravity and friction of the robot, it must overcome a small inertial force to move in compliance with the external force. The principle of torque balance was used to realise the zero-moment dragging and teaching function of the lightweight collaborative robot. The robot parameter identification based on the least square method was used to accurately identify the robot torque sensitivity and friction parameters. When the robot joint rotates at a low speed, it can approximately satisfy the torque balance equation. The experiment uses the joint position and the current motor value collected during the whole moving process under the low-speed dynamic balance as the excitation signal to realise the parameter identification. After the robot was compensated for gravity and static friction, more precise torque control was realised. The zero-moment dragging and teaching function of the robot was more flexible, and the drag process was smoother.

Keywords

Collaborative robot; dynamic; parameter identification; zero-moment; friction

Cite This Article

Chen, S., Yang, J., Cui, G., Niu, F., Yao, B. et al. (2023). Robot Zero-Moment Control Algorithm Based on Parameter Identification of Low-Speed Dynamic Balance. CMES-Computer Modeling in Engineering & Sciences, 134(3), 2021–2039.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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