Systems Theory and Automatic Control

M. Sc. Janine Matschek

Ph.D. Student and Research Assistant

Institute for Automation Engineering (IFAT)
Laboratory for Systems Theory and Automatic Control
Otto-von-Guericke University Magdeburg
39106 Magdeburg, Germany


G07 - 209


(+49) 0391-67 58775


(+49) 0391-67 41191


Research Interests

My current research interests are focused on optimization based control. In particular, I am interested in the following topics:

  • Path Following with Model Predictive Control
  • Gaussian Processes and learning-based Model Predictive Control
  • Force Control and Robotics in Medical Applications


Journals Articles and Book Chapters (all peer reviewed)

[2] J. Matschek, T. Bäthge, T. Faulwasser, and R. Findeisen. Nonlinear Predictive Control for Trajectory Tracking and Path Following: An Introduction and Perspective. Handbook of Model Predictive Control, pages 169--198, 2018.
[1] J. Matschek, E. Bullinger, F. von Haeseler, M. Skalej, and R. Findeisen. Mathematical 3d modelling and sensitivity analysis of multipolar radiofrequency ablation in the spine. Mathematical biosciences, 284:51--60, 2017. [ DOI ]

Proceedings (peer reviewed)

[8] M. Ibrahim, J. Matschek, B. Morabito, and R. Findeisen. Improved area covering in dynamic environments by nonlinear model predictive path following control. In Proceedings of 8th IFAC Symposium on Mechatronic Systems (MECHATRONICS 2019), Vienna, Austria, 2019.
[7] M. Ibrahim, J. Matschek, B. Morabito, and R. Findeisen. Hierarchical model predictive control for autonomous vehicle area coverage. In Proceedings of 21st IFAC Symposium on Automatic Control in Aerospace (ACA 2019), Cranfield, UK, 2019.
[6] J. Bethge, B. Morabito, J. Matschek, and R. Findeisen. Multi-mode learning supported model predictive control with guarantees. In Proceedings of 6th Nonlinear Model Predictive Control Conference (NMPC), pages 616--621, Madison, United States, 2018. [ DOI ]
[5] K. J. Kazim, J. Bethge, J. Matschek, and R. Findeisen. Combined predictive path following and admittance control. In Proceedings of American Control Conference (ACC), pages 3153--3158, Milwaukee, United States, 2018. [ DOI ]
[4] J. Matschek, J. Bethge, P. Zometa, and R. Findeisen. Force feedback and path following using predictive control: Concept and application to a lightweight robot. In Proceedings of 19th IFAC World Congress Toulouse, pages 10243--10248, Toulouse, France, 2017. [ DOI ]
[3] J. Matschek, A. Himmel, F. von Haeseler, E. Bullinger, M. Skalej, and R. Findeisen. Mathematical modelling and sensitivity analysis of multipolar radiofrequency ablation in the spine. In Proceedings of 9th IFAC Symposium on Biological and Medical Systems (BMS), pages 243--248, Berlin, Germany, 2015. [ DOI ]
[2] J. Matschek, F. von Haeseler, and R. Findeisen. Mathematical modeling of mono- and multipolar radio frequency ablation in the spine. In Proceedings of 1st Conference on Image Guided Interventions (IGIC), pages 69--70, Magdeburg, Germany, 2014.
[1] T. Faulwasser, J. Matschek, P. Zometa, and R. Findeisen. Predictive path-following control: Concept and implementation for an industrial robot. In Proc. IEEE Conf. on Cont. Appl., CCA'13, pages 128--133, Hyderabad, India, 2013.

Submitted Proceedings (to be peer reviewed)

[5] J. Matschek, A. Himmel, K. Sundmacher, and R. Findeisen. Constrained Gaussian process learning for model predictive control. 2020. submitted.
[4] J. Matschek, T. Gonschorek, M. Hanses, N. Elkmann, F. Ortmeier, and R. Findeisen. Learning references with Gaussian processes in model predictive control applied to robot assisted surgery. 2020. accepted.
[3] J. Matschek and R. Findeisen. Learning supported Model Predictive Control for Tracking of Periodic References. 2020. submitted.
[2] J. Matschek, R. Jordanowa, and R. Findeisen. Direct Robotic Force Control with Learning Supported Model Predictive Control. 2020. submitted.
[1] H. H. Nguyen, J. Matschek, T. Zieger, A. Savchenko, and R. Findeisen. Towards nominal stability certification of deep learning-based controllers. 2020. accepted.

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Teaching Activity



  • Lecturer for Regelungstechnik (Control Engineering ) (WS 2018/2019)
  • Assistant for Regelungstechnik (Control Engineering) (WS 2017/2018, WS 2016/2017, WS 2015/2016, WS 2014/2015, and WS 2013/2014)
  • Assistant for Regelungstechnik II/Systemtheorie (Control Engineering 2/Systems Theory) (SS2019, SS2018, SS 2017, SS 2016, SS 2015, SS 2014, and SS2013)
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Supervised student projects, Bachelor's and Master's Theses


  • Model predictive Controller Design and Setup of a Franka Emika Robot (P. Holzmann, MA)
  • Model order reduction and validation of 7 DOF robot (B. Dahroug, research project)


  • Lernbasierte MPC mittels Gaußscher Prozessmodelle für Kontaktkräfte in der Robotik (R. Jordanova, MA)
  • Tracking model predictive control for a robotic manipulator (A. Kurmashev, MA)
  • Learning-supported multi-mode force control (P. Eskandar, MA)
  • Cooperative contract based MPC for mobile robots (A. Iakupova, MA)
  • Implementierung eines Gaußschen Prozessmodells mit NARX-Struktur innerhalb einer modellprädiktiven Kontaktkraftregelung (R. Jordanowa, research project)
  • Modellprädiktive Regelung eines Leichtbauroboters zur Bewegungskompensation (S. Fahlbusch, MA)
  • Analyse und Bewertung der Anwendbarkeit von Gaußschen Prozessmodellen auf ein Kontaktszenario in der Robotik (R. Jordanowa, BA)
  • Path-following Control of Small Unmanned Helicopter (P. Stupnitskii and S. Valieva, MA)
  • Gaußsche Regression periodischer Prozesse (S. Fahlbusch, research project)
  • Model predictive hybrid force/position control for path following in robotic applications (J. Bethge, MA)
  • Kinematic Calibration of Lightweight Robot with High Precision Demands (Z. Zhang, MA)
  • Entwicklung einer 3D-Simulation für die bipolare Radiofrequenzablation (F. Fritz, research project)
  • Modellierung und PID Reglerentwurf für Kontakte (C. Kallies, research project)
  • Unscented Kalman filtering of a robotic manipulator (J. Bethge, BA)
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Since April 2013 I have been working as a Ph.D. student and research assistant under the supervision of Prof. Rolf Findeisen at the Institute for Automation Engineering. Until March 2013 I have studied Systems Engineering and Engineering Cybernetics at the Otto-von-Guericke University Magdeburg. The topic of my master thesis was the implementation of a model predictive path following controller on the KUKA LWR in the laboratory of the Institute of Automation Engineering.

Additionally I'm affiliated to the Solution Centre for Image guided local Therapies (Stimulate).
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