@inproceedings{421d1d9adb0e480f9e38cdadf5f25e0d,
title = "Energy-Efficient Control of Bearingless Linear Motors",
abstract = "This paper presents a method to minimize the resistive losses in bearingless linear motors. A minimization algorithm is developed for calculating reference currents for a range of reference forces while the effect of spatial harmonics on force production is considered. The results from the algorithm are implemented in the form of lookup tables and artificial neural networks. A comparison between the two implementation methods is presented. Time-domain simulation results are given for motion control of a bearingless linear flux-switching permanent-magnet motor system while using optimal reference currents. Index Terms-Artificial neural networks, bearingless, energy efficiency, linear actuator, magnetic levitation, table lookup.",
keywords = "Artificial neural networks, bearingless, energy efficiency, linear actuator, magnetic levitation, table lookup",
author = "Reza Hosseinzadeh and Floran Martin and Marko Hinkkanen",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; IEEE International Conference on Mechatronics, ICM ; Conference date: 15-03-2023 Through 17-03-2023",
year = "2023",
month = apr,
day = "17",
doi = "10.1109/ICM54990.2023.10102047",
language = "English",
series = "Proceedings - 2023 IEEE International Conference on Mechatronics, ICM 2023",
publisher = "IEEE",
booktitle = "Proceedings - 2023 IEEE International Conference on Mechatronics, ICM 2023",
address = "United States",
}