Combined current control and system identification of a PMSM with neural ordinary differential equations / by Marvin Meyer ; Supervisor: Wilhelm Kirchgässner and Maximilian Schenke

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Titel
Combined current control and system identification of a PMSM with neural ordinary differential equations / by Marvin Meyer ; Supervisor: Wilhelm Kirchgässner and Maximilian Schenke
Autor
Meyer, Marvin
Beteiligte
Wallscheid, Oliver ; Schenke, Maximilian
Erschienen
Paderborn, 2022
Umfang
1 Online-Ressource (iv, 76 Seiten) : Illustrationen, Diagramme
Hochschulschrift
Universität Paderborn, Masterarbeit, 2022
Anmerkung
Tag der Abgabe: 24.11.2022
Datum der Abgabe
24.11.2022
Sprache
Englisch
Dokumenttyp
Masterarbeit
URN
urn:nbn:de:hbz:466:2-44183
DOI
https://doi.org/10.17619/UNIPB/1-1656

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Abstract

This thesis deals with current control and system identification of a permanent magnet synchronous machine. To learn a data-driven controller for current control, a model of the motor is required. Such model can be constructed with the utilization of neural ordinary differential equations. Through this approach, expert knowledge can be used in combination with learnable parameters to identify the motor parameters. With the help of this model, a neural network can then be trained to control the current. The proposed approach will be compared with both model-based and model-free methods for current control.

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