Master Thesis on Reinforcement Learning-Based Control Concepts for Permanent Magnet Synchronous Machines
11.09.2024
Bosch-Gruppe
Renningen
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Master Thesis on Reinforcement Learning-Based Control Concepts for Permanent Magnet Synchronous Machines
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Master Thesis on Reinforcement Learning-Based Control Concepts for Permanent Magnet Synchronous Machines
Renningen
Aktualität: 11.09.2024
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11.09.2024, Bosch-Gruppe
Renningen
Master Thesis on Reinforcement Learning-Based Control Concepts for Permanent Magnet Synchronous Machines
Aufgaben:
During your assignment, you will develop reinforcement learning-based tracking controller concepts for permanent magnet synchronous machines (PSMs) with offset-free tracking.
You will evaluate the developed controller concepts in simulation in comparison to state-of-the-art controllers.
Last but not least, you will benchmark the developed concepts at the test bench (optional).
Qualifikationen:
Education: studies in the field of Cybernetics, Computer Science, Engineering, Mathematics or comparable
Experience and Knowledge: in machine learning and control theory; MATLAB/Simulink and Python, ideally in DL frameworks; knowledge of electrical machines is a plus
Personality and Working Practice: autonomous, systematic working practice and analytic thinking
Languages: good in German or English
Berufsfeld
Bundesland
Standorte