Research interests
• Mathematical systems and control theory
• Data-driven control [2, 5, 3, 4]
• Model Predictive Control [4]
• Stochastic systems [1]
Research project
• VerneDCt: transforming the power grid from AC to DC (Carl Zeiss Foundation, project number 2011640173)
Short CV
I recieved my Master’s degree in applied mathematics and my Ph. D. degree in mathematics from the Technische Universität Ilmenau in 2015 and 2021. During my doctoral studies I spent five months at the Technische Universität Graz (Austria). In my dissertation supervised by Carsten Trunk I studied spectral properties of differential operators (Sturm–Liouville operators) in Krein spaces and their spectra under perturbation. Currently, I am a postdoctoral researcher at the Technische Universität Ilmenau in the Optimization-based Control group. My research interests include data-driven and model predictive control with application in power grids.
References
[1] Timm Faulwasser, Ruchuan Ou, Guanru Pan, Philipp Schmitz, and Karl Worthmann. Behavioral theory for
stochastic systems? A data-driven journey from Willems to Wiener and back again. Annual Reviews in Control,
2023.
[2] Lukas Lanza, Dario Dennstädt, Philipp Schmitz, Gökcen Devlet Sen, Manuel Schaller, Stephan Trenn, and Karl Worthmann. Control and safe continual learning of nonlinear systems with output constraints. Preprint availabe at arxiv:2303.00523, 2023.
[3] Philipp Schmitz, Alexander Engelmann, Timm Faulwasser, and Karl Worthmann. Data-driven MPC of descriptor systems: A case study for power networks. volume 55, pages 359–364. Elsevier, 2022.
[4] Philipp Schmitz, Timm Faulwasser, and Karl Worthmann. Willems’ fundamental lemma for linear descriptor
systems and its use for data-driven output-feedback MPC. IEEE Control Systems Letters, 2022.
[5] Philipp Schmitz, Lukas Lanza, and Karl Worthmann. Safe data-driven reference tracking with prescribed
performance. In 27th International Conference on System Theory, Control and Computing (ICSTCC), pages
454–460, 2023
