Closed-loop identification method for servo elastic load

被引：1
|
作者：
Zheng L.-K. [1 ]
Wu Y.-X. [1 ]
Wang X.-H. [1 ]
Huang Q.-S. [1 ]
机构：
[1] School of Automation Science and Engineering, South China University of Technology, Guangdong, Guangzhou
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2023年 / 40卷 / 03期
基金：
中国国家自然科学基金;
关键词：
least squares method; mechanical resonance; model reduction; system identification;
D O I：
10.7641/CTA.2022.11058
中图分类号：
学科分类号：
摘要：
The identification for the servo elastic load is an essential step to solve mechanical resonance problem. This paper designs a closed-loop identification method for the two-mass system, which is the most common in industrial application. The current and velocity signals of the motor are collected while the pseudo-random binary sequence is used to stimulate system. On this basis, the least squares method is applied to fit the auto-regressive and moving average model, using a higher fitting order to ensure the accuracy. In order to suppress the influence of sampling noise, a balanced truncation based model reduction method is proposed, which judges the order of the system and extracts dominant states according to the Hankel singular value. In the end, the proposed method is verified by simulation and experiment. The results show that: compared with the traditional identification method, the proposed identification method can effectively suppress noise and has higher accuracy. © 2023 South China University of Technology. All rights reserved.
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收藏
页码：468 / 476
页数：8
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