activity
20192022
most citedData-Driven Modeling and Prediction of Non-Linearizable Dynamics via Spectral Submanifolds

170 citations · 171 across the 2 of their papers we have counts for

collaborators

5 papers

cs.RO20221 cited

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…

math.DS2022

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…

math.DS2022170 cited

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…

math.DS2020

Stability of Forced-Damped Response in Mechanical Systems from a Melnikov Analysis

Mattia Cenedese, George Haller

Frequency responses of multi-degree-of-freedom mechanical systems with weak forcing and damping can be studied as perturbations from their conservative limit. Specifically, recent…

math.DS2019

How do Conservative Backbone Curves Perturb into Forced Responses? A Melnikov Function Analysis

Mattia Cenedese, George Haller

Weakly damped mechanical systems under small periodic forcing tend to exhibit periodic response in a close vicinity of certain periodic orbits of their conservative limit. Specific…