DACS-MFAC-based adaptive prediction method for thermal errors of CNC machine tools under digital twin

被引：0

作者：

Du, Liuqing ^{[1
]}

Lyu, Faliang ^{[1
]}

Yu, Yongwei ^{[1
]}

机构：

[1] College of Mechanical Engineering, Chongqing University of Technology, Chongqing,400054, China

来源：

Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2024年 / 45卷 / 04期

关键词：

The empirical modeling method based on modern control theory is complex to establish a standard thermal error solution for different production conditions of CNC machine tools. Explore the research on adaptive prediction of thermal errors in CNC machine tools using model-free driving under the digital twin framework. Firstly; a digital twin framework based on the thermal sensing-mapping fusion-optimization-drive structure of machine tools is established to achieve the storage and fusion of thermal feature information in the digital twin. Then; based on the assumptions of the MISO system and the dynamic linearization geometric interpretation; a thermal error model free adaptive control (MFAC) method is proposed that is not affected by any structural data of the controlled system. Furthermore; based on the dynamic discovery probability and adaptive step size of the DACS-MFAC algorithm; the system parameters are updated according to a certain period to achieve dynamic optimization of thermal error prediction values in the digital twin system. Experimental result shows that the DACS-MFAC method has advantages such as strong adaptability; high accuracy; and good convergence. © 2024 Science Press. All rights reserved;

D O I：

10.19650/j.cnki.cjsi.J2210477

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页码：248 / 257