TY  - THES
AB  - 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.
AU  - Meyer, Marvin
CY  - Paderborn
DA  - 2022
DO  - 10.17619/UNIPB/1-1656
DP  - Universität Paderborn
LA  - eng
N1  - Tag der Abgabe: 24.11.2022
N1  - Universität Paderborn, Masterarbeit, 2022
PB  - Veröffentlichungen der Universität
PY  - 2022
SP  - 1 Online-Ressource (iv, 76 Seiten)
T2  - Institut für Elektrotechnik und Informationstechnik
TI  - Combined current control and system identification of a PMSM with neural ordinary differential equations
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:466:2-44183
Y2  - 2026-01-19T01:49:26
ER  -