Univ.-Prof. Olaf Stursberg - Research Information System | University of Kassel - CONVERIS Research Information System

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Prof. Dr.-Ing. Olaf Stursberg

Research Areas

Electrical Engineering and Information Engineering

Projects as Co-Investigator

2019 - 2021	Digitalisierung in der Werkstofftechnik (DigiWerk)
09/2017 - 03/2021	Wie zelluläre Uhren biologische Funktionen steuern

Publications

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2022
2021
2021	Hahn, J., Stursberg, O., 2021. Constrained Stochastic Predictive Control of Linear Systems with Uncertain Communication. Automatisierungstechnik 69, 771–781. https://doi.org/10.1515/auto-2021-0033
2021	Liu, Z., Stursberg, O., 2021. Distributed Solution of MIQP Problems Arising for Networked Systems with Coupling Constraints, in: Institute of Electrical and Electronics Engineers -IEEE- (Hrsg.), 2021 European Control Conference (ECC) IEEE, New York, S. 2420–2425. https://doi.org/10.23919/ECC54610.2021.9654996
2021	Liu, Z., Stursberg, O., 2021. Efficient Solution of Distributed MIP in Control of Networked Systems. PAMM Proceedings in Applied Mathematics and Mechanics 20, 1–2. https://doi.org/10.1002/pamm.202000160
2021	Markolf, L., Stursberg, O., 2021. Learning-Based Optimal Control of Constrained Switched Linear Systems Using Neural Networks, in: ICINCO (Hrsg.), 18th International Conference on Informatics in Control, Automation and Robotics. SciTePress , Setúbal, S. 90–98. https://doi.org/10.5220/0010581600900098
2021	Liu, Z., Stursberg, O., 2021. On the Use of MPC Techniques to Decide on Intervention Policies against COVID-19. IFAC-PapersOnLine 54, 502–507. https://doi.org/10.1016/j.ifacol.2021.10.400
2021	Markolf, L., Stursberg, O., 2021. Polytopic Input Constraints in Learning-Based Optimal Control Using Neural Networks, in: Institute of Electrical and Electronics Engineers - IEEE (Hrsg.), European Control Conference (ECC). IEEE, Delft, Netherlands, S. 1018–1023. https://doi.org/10.5220/0010581600900098
2021	Theißen, M., Stursberg, O., 2021. Predictive Control using LPV Techniques for Fast Discrete Time Nonlinear Systems with Changing Setpoints. IFAC-PapersOnLine 288–293. https://doi.org/10.1016/j.ifacol.2021.10.364
2021	Schneegans, J., Eilbrecht, J., Zernetsch, S., Bieshaar, M., Doll, K., Stursberg, O., Sick, B., 2021. Probabilistic VRU Trajectory Forecasting for Model-Predictive Planning - a Case Study: Overtaking Cyclists, in: Institute of Electrical and Electronics Engineers - IEEE (Hrsg.), IEEE Intelligent Vehicles Symposium Workshops (IV Workshops). IEEE, Nagoya, Japan, S. 272–279. https://doi.org/ 10.1109/IVWorkshops54471.2021.9669208