Identification and compensation of friction for modular joints based on grey wolf optimizer

被引：0
|
作者：
Cui J.-K. [1 ,2 ]
Sai H.-Y. [1 ,2 ]
Zhang E.-Y. [1 ]
Zhu M.-C. [1 ]
Xu Z.-B. [1 ,2 ,3 ]
机构：
[1] Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun
[2] University of Chinese Academy of Sciences, Beijing
[3] Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing
来源：
Guangxue Jingmi Gongcheng/Optics and Precision Engineering | 2021年 / 29卷 / 11期
关键词：
Friction compensation; Grey wolf optimizer; LuGre friction model; Modular joint; Parameter identification;
D O I：
10.37188/OPE.20212911.2683
中图分类号：
学科分类号：
摘要：
To identify the friction model parameters of a modular joint, an off-line identification method that compensates the joint friction is proposed. First, the structure and control system of the modular joint are presented, and the dynamic model of the joint is established. Second, the LuGre friction model is developed. The grey wolf algorithm and piecewise least-square algorithm with a pseudo random sequence are then used to identify the respective model parameters. The results of two methods are compared and analyzed, and a feed-forward compensation algorithm based on the LuGre friction model is designed and verified experimentally. The experimental results indicate that compared with the piecewise least-square method, the identification accuracy of the grey wolf algorithm improved by 19.2%; the joint velocity tracking error decreased from 0.295 (°)/s to 0.183 (°)/s when the given velocity signal was a sine wave with an amplitude of 1 (°)/s and a frequency of 10 Hz; and the velocity loop bandwidth increased from 12 Hz to 18 Hz after friction compensation. Several experiments are repeated, and the identified data exhibit a high repeatability, which verifies the suitability of the proposed method. The proposed feed-forward friction compensation algorithm can be used to improve the dynamic performance of the joint control system. © 2021, Science Press. All right reserved.
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页码：2683 / 2691
页数：8
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