Learning networked dynamical system models with weak form and graph neural networks
This paper presents a sequence of two approaches for the data-driven control-oriented
modeling of networked systems, ie, the systems that involve many interacting dynamical …
modeling of networked systems, ie, the systems that involve many interacting dynamical …
Multi-Timescale System Separation via Data-Driven Identification Within a Singular Perturbation Framework
This paper presents a timescale separation method for realization-preserving reduced-order
modeling of dynamic systems. While classical singular perturbation theory can be used to …
modeling of dynamic systems. While classical singular perturbation theory can be used to …
Global Description of Flutter Dynamics via Koopman Theory
We introduce a data-driven method for flutter analysis and prediction based on Koopman
theory. The Koopman formalism enables the representation of nonlinear dynamics in a …
theory. The Koopman formalism enables the representation of nonlinear dynamics in a …
Parametrized Global Linearization Models for Flutter Prediction
We present a data-driven flutter analysis and prediction method based on the Koopman
theory. The Koopman formalism represents nonlinear dynamics in a higher-dimensional …
theory. The Koopman formalism represents nonlinear dynamics in a higher-dimensional …