Improved Prediction Model of the Friction Error of CNC Machine Tools Based on the Long Short Term Memory Method
Abstract
:1. Introduction
2. Model-Based Tracking Error Prediction
3. Prediction of the Nonlinear Friction Error
3.1. Achieving the Nonlinear Friction Error Based on the Transfer Function
3.2. Nonlinear Friction Error Prediction Model Based on the LSTM
3.2.1. Selection of Neural Network Models
3.2.2. Design of the LSTM
3.3. Accurate Prediction of the Tracking Error Based on the Combined Model of the Transfer Function and LSTM
4. Experimental Results
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Wang, T.; Zhang, D. Improved Prediction Model of the Friction Error of CNC Machine Tools Based on the Long Short Term Memory Method. Machines 2023, 11, 243. https://doi.org/10.3390/machines11020243
Wang T, Zhang D. Improved Prediction Model of the Friction Error of CNC Machine Tools Based on the Long Short Term Memory Method. Machines. 2023; 11(2):243. https://doi.org/10.3390/machines11020243
Chicago/Turabian StyleWang, Tao, and Dailin Zhang. 2023. "Improved Prediction Model of the Friction Error of CNC Machine Tools Based on the Long Short Term Memory Method" Machines 11, no. 2: 243. https://doi.org/10.3390/machines11020243