8 Publications

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[8]
2022 | Conference Paper | LibreCat-ID: 40212 LibreCat
 
[7]
2021 | Journal Article | LibreCat-ID: 22162
Transferring Online Reinforcement Learning for Electric Motor Control From Simulation to Real-World Experiments
G. Book, A. Traue, P. Balakrishna, A. Brosch, M. Schenke, S. Hanke, W. Kirchgässner, O. Wallscheid, IEEE Open Journal of Power Electronics (2021) 187–201.
LibreCat | DOI
 
[6]
2021 | Journal Article | LibreCat-ID: 21254
gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems
P. Balakrishna, G. Book, W. Kirchgässner, M. Schenke, A. Traue, O. Wallscheid, Journal of Open Source Software (2021).
LibreCat | DOI
 
[5]
2021 | Journal Article | LibreCat-ID: 25031
A Deep Q-Learning Direct Torque Controller for Permanent Magnet Synchronous Motors
M. Schenke, O. Wallscheid, IEEE Open Journal of the Industrial Electronics Society (2021) 388–400.
LibreCat | DOI
 
[4]
2021 | Journal Article | LibreCat-ID: 29662 LibreCat
 
[3]
2019 | Journal Article | LibreCat-ID: 25030
Controller Design for Electrical Drives by Deep Reinforcement Learning: A Proof of Concept
M. Schenke, W. Kirchgässner, O. Wallscheid, IEEE Transactions on Industrial Informatics (2019) 4650–4658.
LibreCat | DOI
 
[2]
2018 | Conference Paper | LibreCat-ID: 29628
Improving torque and speed estimation accuracy by conjoint parameter identification and unscented Kalman filter design for induction machines
O. Wallscheid, M. Schenke, J. Böcker, in: 2018 21st International Conference on Electrical Machines and Systems (ICEMS), 2018, pp. 1181–1186.
LibreCat
 
[1]
2018 | Conference Paper | LibreCat-ID: 29625
A combined approach to identify induction machine parameters and to design an extended kalman filter for speed and torque estimation
O. Wallscheid, M. Schenke, J. Böcker, in: 2018 IEEE 18th International Power Electronics and Motion Control Conference (PEMC), 2018, pp. 793–799.
LibreCat
 

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8 Publications

Mark all

[8]
2022 | Conference Paper | LibreCat-ID: 40212 LibreCat
 
[7]
2021 | Journal Article | LibreCat-ID: 22162
Transferring Online Reinforcement Learning for Electric Motor Control From Simulation to Real-World Experiments
G. Book, A. Traue, P. Balakrishna, A. Brosch, M. Schenke, S. Hanke, W. Kirchgässner, O. Wallscheid, IEEE Open Journal of Power Electronics (2021) 187–201.
LibreCat | DOI
 
[6]
2021 | Journal Article | LibreCat-ID: 21254
gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems
P. Balakrishna, G. Book, W. Kirchgässner, M. Schenke, A. Traue, O. Wallscheid, Journal of Open Source Software (2021).
LibreCat | DOI
 
[5]
2021 | Journal Article | LibreCat-ID: 25031
A Deep Q-Learning Direct Torque Controller for Permanent Magnet Synchronous Motors
M. Schenke, O. Wallscheid, IEEE Open Journal of the Industrial Electronics Society (2021) 388–400.
LibreCat | DOI
 
[4]
2021 | Journal Article | LibreCat-ID: 29662 LibreCat
 
[3]
2019 | Journal Article | LibreCat-ID: 25030
Controller Design for Electrical Drives by Deep Reinforcement Learning: A Proof of Concept
M. Schenke, W. Kirchgässner, O. Wallscheid, IEEE Transactions on Industrial Informatics (2019) 4650–4658.
LibreCat | DOI
 
[2]
2018 | Conference Paper | LibreCat-ID: 29628
Improving torque and speed estimation accuracy by conjoint parameter identification and unscented Kalman filter design for induction machines
O. Wallscheid, M. Schenke, J. Böcker, in: 2018 21st International Conference on Electrical Machines and Systems (ICEMS), 2018, pp. 1181–1186.
LibreCat
 
[1]
2018 | Conference Paper | LibreCat-ID: 29625
A combined approach to identify induction machine parameters and to design an extended kalman filter for speed and torque estimation
O. Wallscheid, M. Schenke, J. Böcker, in: 2018 IEEE 18th International Power Electronics and Motion Control Conference (PEMC), 2018, pp. 793–799.
LibreCat
 

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