Prediction and compensation of contour error of CNC systems based on LSTM neural-network

Li, Jiangang, Qi, Changgui, Li, Yanan and Wu, Zenghao (2021) Prediction and compensation of contour error of CNC systems based on LSTM neural-network. IEEE-ASME Transactions on Mechatronics. ISSN 1083-4435

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Abstract

This 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.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 22 Mar 2021 08:04
Last Modified: 30 Mar 2021 09:30
URI: http://sro.sussex.ac.uk/id/eprint/97966

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