Master Thesis on Reinforcement Learning-Based Control Concepts for Permanent Magnet Synchronous Machines
Master Thesis on Reinforcement Learning-Based Control Concepts for Permanent Magnet Synchronous Machines
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Job Description
- During your assignment you will develop reinforcement learningbased tracking controller concepts for permanent magnet synchronous machines (PSMs) with offsetfree tracking.
- You will evaluate the developed controller concepts in simulation in comparison to stateoftheart controllers.
- Last but not least you will benchmark the developed concepts at the test bench (optional).
Qualifications :
- 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
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.
Need further information about the job
Felix Berkel (Functional Department)
49 1
Maximilian Manderla (Functional Department)
49
#LIDNI
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
