16 papers · 1 filter
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…
Limitations of LTI Koopman Modeling for Nonlinear Control Systems
Johannes Heeg, Karl Worthmann
Koopman operator theory yields powerful tools for modeling, analysis, and control of nonlinear dynamical systems. Prominently, linear time-invariant (LTI) Koopman representations h…
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…
Data-driven Model Predictive Control: Asymptotic Stability despite Approximation Errors exemplified in the Koopman framework
Irene Schimperna, Karl Worthmann, Manuel Schaller +2
In this paper, we analyze stability of nonlinear model predictive control (MPC) using data-driven surrogate models in the optimization step. First, we establish asymptotic stabilit…
Spatial exponential decay of perturbations in optimal control of general evolution equations
Simone Göttlich, Benedikt Oppeneiger, Manuel Schaller +1
We analyze the robustness of optimally controlled evolution equations with respect to spatially localized perturbations. We prove that if the involved operators are domain-uniforml…
Kernel-based Koopman approximants for control: Flexible sampling, error analysis, and stability
Lea Bold, Friedrich M. Philipp, Manuel Schaller +1
Data-driven techniques for analysis, modeling, and control of complex dynamical systems are on the uptake. Koopman theory provides the theoretical foundation for the popular kernel…