1.9k citations · 5.7k across the 37 of their papers we have counts for
40 papers
Learning Nonlinear Projections for Reduced-Order Modeling of Dynamical Systems using Constrained Autoencoders
Samuel E. Otto, Gregory R. Macchio, Clarence W. Rowley
Recently developed reduced-order modeling techniques aim to approximate nonlinear dynamical systems on low-dimensional manifolds learned from data. This is an effective approach fo…
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…
Continuous-time balanced truncation for time-periodic fluid flows using frequential Gramians
Alberto Padovan, Clarence W. Rowley
Reduced-order models for flows that exhibit time-periodic behavior are critical for several tasks, including active control and optimization. One well-known procedure to obtain the…
Model Reduction for Nonlinear Systems by Balanced Truncation of State and Gradient Covariance
Samuel E. Otto, Alberto Padovan, Clarence W. Rowley
Data-driven reduced-order models often fail to make accurate forecasts of high-dimensional nonlinear dynamical systems that are sensitive along coordinates with low-variance becaus…
Optimal Control with Learning on the Fly: System with Unknown Drift
Daniel Gurevich, Debdipta Goswami, Charles L. Fefferman +1
This paper derives an optimal control strategy for a simple stochastic dynamical system with constant drift and an additive control input. Motivated by the example of a physical sy…
Controlling Unknown Linear Dynamics with Bounded Multiplicative Regret
Jacob Carruth, Maximilian F. Eggl, Charles Fefferman +2
We consider a simple control problem in which the underlying dynamics depend on a parameter that is unknown and must be learned. We exhibit a control strategy which is optimal to w…