5 papers
Data-driven feedback rectification of switched linear systems
Philipp Schmitz, Hannes Gernandt, Maria C. Honecker +1
In this paper, a data-driven method for the computation of stabilizing state-feedbacks is proposed that leads to a rectified eigenstructure of switched linear systems. This means t…
Excitation of control-affine systems and Koopman error bounds
Philipp Schmitz, Lea Bold, Friedrich M. Philipp +4
The Koopman operator and extended dynamic mode decomposition (EDMD) as a data-driven technique for its approximation have attracted considerable attention as a key tool for modelin…
A data-based image representation for continuous-time LTI systems
Amine Othmane, Philipp Schmitz, Karl Worthmann +1
We derive a numerically stable method to compute an image representation of an unknown linear system only from data, leveraging a continuous-time version of Willems et al.'s fundam…
Sampled-data funnel control and its use for safe continual learning
Lukas Lanza, Dario Dennstädt, Karl Worthmann +4
We propose a novel sampled-data output-feedback controller for nonlinear systems of arbitrary relative degree that ensures reference tracking within prescribed error bounds. We pro…
Towards Data-Driven Multi-Stage OPF
Oleksii Molodchyk, Philipp Schmitz, Alexander Engelmann +2
The operation of large-scale power systems is usually scheduled ahead via numerical optimization. However, this requires models of grid topology, line parameters, and bus specifica…