Thesis in Reinforcement Learning-Based Control Concepts for Electrical Drives
Job Description
- During your thesis you will develop the 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 and comparison to state-of-the-art controllers.
- Last but not least, you will benchmark the developed concepts at the test bench (optional).
Qualifications
- Education : studies in the field of or comparable Cybernetics, Computer Science, Engineering, Mathematics
- Experience and Knowledge : profound knowledge of machine learning and control theory, with a nice to have knowledge of electrical machines;
experience in Matlab / Simulink and Python, ideally in DL frameworks
- Personality and Working Practice : autonomous, systematic working practice and analytic thinking
- Languages : good in English or German
Additional Information
Start : according to prior agreement
Duration : 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.
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Felix Berkel (Functional Department)
49 711 811 92301
Maximilian Manderla (Functional Department)
49 711 811 7297
LI-DNI
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