17 citations · 29 across the 6 of their papers we have counts for
9 papers · 1 filter
Koopman meets input-output data: Data-driven output-feedback control of nonlinear systems with closed-loop guarantees
Robin Strässer, Julian Berberich, Manuel Schaller +2
Data-driven control of nonlinear systems from input-output measurements remains a fundamental challenge, as existing approaches with rigorous closed-loop guarantees predominantly r…
An overview of Koopman-based control: From error bounds to closed-loop guarantees
Robin Strässer, Karl Worthmann, Igor MeziÄ +3
Controlling nonlinear dynamical systems remains a central challenge in a wide range of applications, particularly when accurate first-principle models are unavailable. Data-driven…
SafEDMD: A Koopman-based data-driven controller design framework for nonlinear dynamical systems
Robin Strässer, Manuel Schaller, Karl Worthmann +2
The Koopman operator serves as the theoretical backbone for machine learning of dynamical control systems, where the operator is heuristically approximated by extended dynamic mode…
Energy-optimal control of discrete-time port-Hamiltonian systems
Arijit Sarkar, Vaibhav Kumar Singh, Manuel Schaller +1
In this letter, we study the energy-optimal control of nonlinear port-Hamiltonian (pH) systems in discrete time. For continuous-time pH systems, energy-optimal control problems are…
Koopman-based control of nonlinear systems with closed-loop guarantees
Robin Strässer, Julian Berberich, Manuel Schaller +2
In this paper, we provide a tutorial overview and an extension of a recently developed framework for data-driven control of unknown nonlinear systems with rigorous closed-loop guar…
Kernel-based error bounds of bilinear Koopman surrogate models for nonlinear data-driven control
Robin Strässer, Manuel Schaller, Julian Berberich +2
We derive novel deterministic bounds on the approximation error of data-based bilinear surrogate models for unknown nonlinear systems. The surrogate models are constructed using ke…