3 papers
math.OC2024
Extracting Koopman Operators for Prediction and Control of Non-linear Dynamics Using Two-stage Learning and Oblique Projections
Daisuke Uchida, Karthik Duraisamy
The Koopman operator framework provides a perspective that non-linear dynamics can be described through the lens of linear operators acting on function spaces. As the framework nat…
math.OC2024
Data-driven Koopman Operator-based Prediction and Control Using Model Averaging
Daisuke Uchida, Karthik Duraisamy
This work presents a data-driven Koopman operator-based modeling method using a model averaging technique. While the Koopman operator has been used for data-driven modeling and con…
math.OC2024
Model Predictive Control of Nonlinear Dynamics Using Online Adaptive Koopman Operators
Daisuke Uchida, Karthik Duraisamy
This paper develops a methodology for adaptive data-driven Model Predictive Control (MPC) using Koopman operators. While MPC is ubiquitous in various fields of engineering, the con…