23 citations
- Paderborn UniversityDE19 papers
- Association for Computational LinguisticsUS1 paper
- Friedrich Schiller University JenaDE1 paper
- Google (United States)US1 paper
- Heinrich Heine University DüsseldorfDE1 paper
- Institute of Informatics of the Slovak Academy of SciencesSK1 paper
- Maastricht UniversityNL1 paper
- Max Planck Institute for InformaticsDE1 paper
- Quantitative BioSciencesUS1 paper
- Technische Universität BerlinDE1 paper
- Technische Universität BraunschweigDE1 paper
4 papers · 1 filter
Adaptive Koopman-Based Models for Holistic Controller and Observer Design
Annika Junker, Keno Pape, Julia Timmermann +1
We present a method to obtain a data-driven Koopman operator-based model that adapts itself during operation and can be straightforwardly used for the controller and observer desig…
Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems
Oliver Schön, Ricarda-Samantha Götte, Julia Timmermann
While trade-offs between modeling effort and model accuracy remain a major concern with system identification, resorting to data-driven methods often leads to a complete disregard…
Learning Data-Driven PCHD Models for Control Engineering Applications
Annika Junker, Julia Timmermann, Ansgar Trächtler
The design of control engineering applications usually requires a model that accurately represents the dynamics of the real system. In addition to classical physical modeling, powe…
Data-Driven Models for Control Engineering Applications Using the Koopman Operator
Annika Junker, Julia Timmermann, Ansgar Trächtler
Within this work, we investigate how data-driven numerical approximation methods of the Koopman operator can be used in practical control engineering applications. We refer to the…