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Prediction and compensation of contour error of CNC systems based on LSTM neural-network
journal contribution
posted on 2023-06-09, 23:24 authored by Jiangang Li, Changgui Qi, Yanan LiYanan Li, Zenghao WuThis paper proposes a contour error estimation and compensation method for computer numerical control (CNC) systems based on the long short-term memory neural network (LSTM-NN). This is achieved by performing modeling of each axis to predict the tracking error, calculating the actual trajectory, estimating the contour error, and modifying the reference trajectory. First, linear feature selection based on a simplified single-axis model and nonlinear feature selection based on a circular test are performed to achieve tracking error prediction. Then, a spline-approximation-based contour error estimation method is proposed to estimate the contour error between the reference trajectory and the predicted trajectory. Finally, contour error compensation is performed on the reference trajectory before it is run on CNC systems. The proposed method is validated through experiments on a three-axis CNC system.
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Publication status
- Published
File Version
- Accepted version
Journal
IEEE/ASME Transactions on MechatronicsISSN
1083-4435Publisher
Institute of Electrical and Electronics EngineersExternal DOI
Department affiliated with
- Engineering and Design Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2021-03-22First Open Access (FOA) Date
2021-03-30First Compliant Deposit (FCD) Date
2021-03-22Usage metrics
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