Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories

Samuel E. Otto, Sebastian Peitz, Clarence W. Rowley

Data-driven models for nonlinear dynamical systems based on approximating the underlying Koopman operator or generator have proven to be successful tools for forecasting, feature l…