Abstract
This talk presents recent advances in data-driven controller design for nonlinear dynamical systems, with a focus on ensuring closed-loop stability via Koopman operator theory. The Koopman operator enables the reformulation of a nonlinear control-affine system as an infinite-dimensional bilinear system, which can be approximated using Extended Dynamic Mode Decomposition (EDMD) with finite data and a finite dictionary. By integrating robust control strategies, we develop purely data-driven state-feedback controllers that explicitly account for approximation errors. In particular, we discuss the Stability- and certificate-oriented EDMD (SafEDMD) framework alongside a kernel-based EDMD variant, both yielding finite-dimensional bilinear surrogate models. Based on these data-driven, error-affected representations, we provide rigorous closed-loop guarantees through proportional error bounds, thereby enabling reliable controller design for nonlinear systems. This approach leads to a nonlinear controller parameterization that can be efficiently computed using semidefinite programming. Numerical examples demonstrate the effectiveness of the proposed methods and highlight their advantages over existing Koopman-based control approaches.
Biographical Information
Robin Strässer is currently a PhD student at the Institute for Systems Theory and Automatic Control at the University of Stuttgart under the supervision of Prof. Frank Allgöwer. He received a master’s degree in Simulation Technology from the University of Stuttgart, Germany, in 2020. During his M.Sc., he spent six months at University of California, Santa Barbara, where he also carried out the research for his master’s thesis under the supervision of Prof. James Rawlings. Since 2020, he has been a research and teaching assistant at the Institute for Systems Theory and Automatic Control and a member of the Graduate School Simulation Technology at the University of Stuttgart. His research interests include data-driven system analysis and control, with a focus on nonlinear systems, in particular by using the Koopman operator to obtain bilinear surrogate models with error certificates. Robin Strässer received the Best Poster Award at the International Conference on Data-Integrated Simulation Science (SimTech2023) and the Best Paper Award at the European Robotics Forum (ERF2025).