Advisor(s):
Sebastian Trimpe
After receiving my diploma in electrical engineering from TU Dresden, I joined the Max Planck Institute for Intelligent Systems in 2017. My research focuses on control of cyber-physical systems. Cyber-physical systems are envisioned to integrate physical processes with computing and communication and to act autonomously in the real world, collaborating with each other and with humans. To realize this vision, I work on enabling provably stable and resource-efficient control of systems that are connected over (typically wireless) communication networks. As for systems that are meant to act autonomously in the real world foreseeing all possible situations they may face already at design time is not possible, I also investigate how we can leverage machine learning techniques to enhance their flexibility. At the MPI, I am part of the Intelligent Control Systems Group and am supervised by Sebastian Trimpe. In addition, I am part of the Division of Decision and Control Systems at KTH Stockholm, where I work with Karl Henrik Johansson, who is the co-supervisor of my thesis.
Presentation of our paper 'Feedback Control goes Wireless: Guaranteed stability over Low-power Multi-hop Networks' at the 10th ACM/IEEE International Conference on Cyber-Physical Systems.
The ability to learn is an essential aspect of future intelligent systems that are facing uncertain environments. However, the process of learning a new model or behavior often does not come for free, but involves a certain cost. For example, gathering informative data can be challenging due to physical limitations, or updating mode...
Future intelligent systems such as autonomous robots, self-driving cars, or manufacturing systems will be connected over communication networks. Facilitated by the network, the individual agents can coordinate their actions and thus achieve functionality exceeding the individual unit (for example, driving in formation or collaborati...
Sebastian Trimpe Simon Ebner Dominik Baumann Friedrich Solowjow
Cyber-physical systems (CPS) tightly integrate physical processes with computing and communication, thus, enabling emerging applications such as coordinated flight of autonomous vehicles or controlling factory automation machinery over wireless networks. The adoption of wireless technology offers unprecedented flexibility in sharing...
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Baumann, D., Mager, F., Zimmerling, M., Trimpe, S.
Control-guided Communication: Efficient Resource Arbitration and Allocation in Multi-hop Wireless Control Systems
IEEE Control Systems Letters, 4(1):127-132, January 2020 (article) To be published
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Baumann, D., Solowjow, F., Johansson, K. H., Trimpe, S.
Event-triggered Pulse Control with Model Learning (if Necessary)
In Proceedings of the American Control Conference, American Control Conference (ACC), July 2019 (inproceedings) Accepted
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Trimpe, S., Baumann, D.
Resource-aware IoT Control: Saving Communication through Predictive Triggering
IEEE Internet of Things Journal, 6(3):5013-5028, June 2019 (article)
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Mager, F., Baumann, D., Jacob, R., Thiele, L., Trimpe, S., Zimmerling, M.
Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks
In Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems, pages: 97-108, 10th ACM/IEEE International Conference on Cyber-Physical Systems, April 2019 (inproceedings)
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Mager, F., Baumann, D., Jacob, R., Thiele, L., Trimpe, S., Zimmerling, M.
Demo Abstract: Fast Feedback Control and Coordination with Mode Changes for Wireless Cyber-Physical Systems
Proceedings of the 18th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), pages: 340-341, 18th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), April 2019 (poster)
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Baumann, D.
Fast and Resource-Efficient Control of Wireless Cyber-Physical Systems
KTH Royal Institute of Technology, Stockholm, Febuary 2019 (phdthesis)
al
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Baumann, D., Zhu, J., Martius, G., Trimpe, S.
Deep Reinforcement Learning for Event-Triggered Control
In Proceedings of the 57th IEEE International Conference on Decision and Control (CDC), pages: 943-950, 57th IEEE International Conference on Decision and Control (CDC), December 2018 (inproceedings)
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Solowjow, F., Baumann, D., Garcke, J., Trimpe, S.
Event-triggered Learning for Resource-efficient Networked Control
In Proceedings of the American Control Conference (ACC), pages: 6506 - 6512, American Control Conference, June 2018 (inproceedings)
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Mager, F., Baumann, D., Trimpe, S., Zimmerling, M.
Poster Abstract: Toward Fast Closed-loop Control over Multi-hop Low-power Wireless Networks
Proceedings of the 17th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), pages: 158-159, Porto, Portugal, April 2018 (poster)
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Baumann, D., Mager, F., Singh, H., Zimmerling, M., Trimpe, S.
Evaluating Low-Power Wireless Cyber-Physical Systems
In Proceedings of the IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), pages: 13-18, IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), April 2018 (inproceedings)
am
Ascoli, A., Baumann, D., Tetzlaff, R., Chua, L. O., Hild, M.
Memristor-enhanced humanoid robot control system–Part I: theory behind the novel memcomputing paradigm
International Journal of Circuit Theory and Applications, 46(1):155-183, 2018 (article)
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Baumann, D., Ascoli, A., Tetzlaff, R., Chua, L. O., Hild, M.
Memristor-enhanced humanoid robot control system–Part II: circuit theoretic model and performance analysis
International Journal of Circuit Theory and Applications, 46(1):184-220, 2018 (article)
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