A hybrid twin based on machine learning enhanced reduced order model for real-time simulation of magnetic bearings

A hybrid twin based on machine learning enhanced reduced order model for real-time simulation of magnetic bearings

Abstract The simulation of magnetic bearings involves highly non-linear physics, with high dependency on the input variation. Moreover, such a simulation is time consuming and can’t run, within realistic computation time for control purposes, when using classical computation methods. On the other ha...

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Bibliographic Details
Main Authors: Chady Ghnatios, Sebastian Rodriguez, Jerome Tomezyk, Yves Dupuis, Joel Mouterde, Joaquim Da Silva, Francisco Chinesta
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Advanced Modeling and Simulation in Engineering Sciences
Subjects:
Spectral method
Reduced basis
Machine learning
Magnetic bearing
Magnetic levitation
Long-short term memory
Online Access:https://doi.org/10.1186/s40323-024-00258-2

Internet

https://doi.org/10.1186/s40323-024-00258-2

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