{"title":"In-process identification of feed drive dynamics considering machining forces","authors":"J.D. McPherson, M. Mehrabi, K. Ahmadi","doi":"10.1016/j.precisioneng.2025.04.027","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents a new closed-loop dynamics model for ballscrew feed drives in CNC machine tools, enabling non-intrusive, in-process model calibration and motion prediction even in the presence of unmeasured machining forces. The presented model employs a Partially Linear Auto-Regressive with Exogenous input (PL-ARX) structure, where the linear component captures the servo drive and rigid-body dynamics, and the nonlinear component represents unknown machining forces. Kernel-based regression is then used to simultaneously identify the linear dynamics and machining force disturbances from internal controller signals during milling.</div><div>The model is validated on two different CNC machines under experimental milling conditions. Results confirm the approach accurately identifies unbiased linear dynamics despite unmeasured disturbances and achieves precise online motion prediction. These capabilities are critical for enabling real-time feedrate optimization and model-predictive control in advanced machining systems.</div></div>","PeriodicalId":54589,"journal":{"name":"Precision Engineering-Journal of the International Societies for Precision Engineering and Nanotechnology","volume":"95 ","pages":"Pages 468-483"},"PeriodicalIF":3.5000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Precision Engineering-Journal of the International Societies for Precision Engineering and Nanotechnology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0141635925001461","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a new closed-loop dynamics model for ballscrew feed drives in CNC machine tools, enabling non-intrusive, in-process model calibration and motion prediction even in the presence of unmeasured machining forces. The presented model employs a Partially Linear Auto-Regressive with Exogenous input (PL-ARX) structure, where the linear component captures the servo drive and rigid-body dynamics, and the nonlinear component represents unknown machining forces. Kernel-based regression is then used to simultaneously identify the linear dynamics and machining force disturbances from internal controller signals during milling.
The model is validated on two different CNC machines under experimental milling conditions. Results confirm the approach accurately identifies unbiased linear dynamics despite unmeasured disturbances and achieves precise online motion prediction. These capabilities are critical for enabling real-time feedrate optimization and model-predictive control in advanced machining systems.
期刊介绍:
Precision Engineering - Journal of the International Societies for Precision Engineering and Nanotechnology is devoted to the multidisciplinary study and practice of high accuracy engineering, metrology, and manufacturing. The journal takes an integrated approach to all subjects related to research, design, manufacture, performance validation, and application of high precision machines, instruments, and components, including fundamental and applied research and development in manufacturing processes, fabrication technology, and advanced measurement science. The scope includes precision-engineered systems and supporting metrology over the full range of length scales, from atom-based nanotechnology and advanced lithographic technology to large-scale systems, including optical and radio telescopes and macrometrology.