170 citations · 301 across the 10 of their papers we have counts for
4 papers · 1 filter
Data-Driven Spectral Submanifold Reduction for Nonlinear Optimal Control of High-Dimensional Robots
John Irvin Alora, Mattia Cenedese, Edward Schmerling +2
Modeling and control of high-dimensional, nonlinear robotic systems remains a challenging task. While various model- and learning-based approaches have been proposed to address the…
Fast data-driven model reduction for nonlinear dynamical systems
Joar Axås, Mattia Cenedese, George Haller
We present a fast method for nonlinear data-driven model reduction of dynamical systems onto their slowest nonresonant spectral submanifolds (SSMs). We use observed data to locate…
Dynamics-based machine learning of transitions in Couette flow
Bálint Kaszás, Mattia Cenedese, George Haller
We derive low-dimensional, data-driven models for transitions among exact coherent states (ECSs) in one of the most studied canonical shear flows, the plane Couette flow. These one…
Data-Driven Modeling and Prediction of Non-Linearizable Dynamics via Spectral Submanifolds
Mattia Cenedese, Joar Axås, Bastian Bäuerlein +2
We develop a methodology to construct low-dimensional predictive models from data sets representing essentially nonlinear (or non-linearizable) dynamical systems with a hyperbolic…