Work

Koopman-based Control for Stochastic Systems: Application to Enhanced Sampling

Year: 2025

Type: article

Abstract: We present a data-driven approach to use the Koopman generator for prediction and optimal control of control-affine stochastic systems. We provide a novel conceptual approach and a proof-of-principle for the determination of optimal control policies which accelerate the simulation of rare events in metastable stochastic systems.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2025.03.049

Authors: Lei Guo, Jan Heiland, Feliks Nüske

Institutions: Max Planck Institute for Dynamics of Complex Technical Systems, Otto-von-Guericke-Universität Magdeburg, Technische Universität Ilmenau

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: diamond

Funder: Deutsche Forschungsgemeinschaft

OpenAlex ID: W4408886165

FWCI:

Cites: 18

Cited by:

Related to: 10