M.Sc. Tim Zieger
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Ph.D. Student
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Research Interests
- Neural network supported model predictive control
- Stability of neural network interconnected Systems
- Machine learning methods for model identification
| [6] | T. Zieger, P. Holzmann, J. Bethge, T. Oehlschl"gel, and R. Findeisen. Rigid-tube nonlinear model predictive control for path following. In Proceedings of IFAC World Congress, 2023. accepted. |
| [5] | H. H. Nguyen, T. Zieger, S. C. Wells, A. Nikolakopoulou, R. D. Braatz, and R. Findeisen. Stability certificates for neural network learning-based controllers using robust control theory. In 2021 American Control Conference (ACC), pages 3564--3569, New Orleans, USA, 2021. |
| [4] | H. H. Nguyen, T. Zieger, R. D. Braatz, and R. Findeisen. Robust control theory based stability certificates for neural network approximated nonlinear model predictive control. In Proceedings of 7th Nonlinear Model Predictive Control Conference (NMPC), pages 347--352, Bratislava, Slovakia, 2021. |
| [3] | T. Zieger, A. Savchenko, T. Oehlschlägel, and R. Findeisen. One-step safe neural network supported control. In 2021 American Control Conference (ACC), New Orleans, USA, 2021. |
| [2] | H. H. Nguyen, J. Matschek, T. Zieger, A. Savchenko, N. Noroozi, and R. Findeisen. Towards nominal stability certification of deep learning-based controllers. In 2020 American Control Conference (ACC), pages 3886--3891, Denver, CO, USA, 2020. |
| [1] | T. Zieger, A. Savchenko, T. Oehlschlägel, and R. Findeisen. Towards safe neural network supported model predictive control. Berlin, Germany, 2020. |
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Teaching Activity
Courses:
- Assistant for Regelungstechnik (Control Engineering) WS 2020/2021
- Assistant for Machine Learning, Dynamic Systems, and Control (SS 2020)
Thesis and Student Projects
If you are interested in doing your thesis on Model Predictive Control in the context of robotics or autonomous driving, don't hesitate to contact me!
Send me a short e-mail with the following information, this may increase your chances of being considered as a candidate:
- a brief description of who you are: name, study program, time planned for developing the project,
- A transcript of your grades from Bachelor and Master studies (pdf-file),
- which project are you interested in,
- a clear statement of why you think you could succesfully complete the project,
- A curriculum vitae (max. one page) with the information that is relevant to the project (do not include hobbies or primary school info, for example) (pdf-file).