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Main Authors: Yang, Antony, Axås, Joar, Kádár, Fanni, Stépán, Gábor, Haller, George
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.08893
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_version_ 1866916285429841920
author Yang, Antony
Axås, Joar
Kádár, Fanni
Stépán, Gábor
Haller, George
author_facet Yang, Antony
Axås, Joar
Kádár, Fanni
Stépán, Gábor
Haller, George
contents We introduce a method for constructing reduced-order models directly from videos of dynamical systems. The method uses a non-intrusive tracking to isolate the motion of a user-selected part in the video of an autonomous dynamical system. In the space of delayed observations of this motion, we reconstruct a low-dimensional attracting spectral submanifold (SSM) whose internal dynamics serves as a mathematically justified reduced-order model for nearby motions of the full system. We obtain this model in a simple polynomial form that allows explicit identification of important physical system parameters, such as natural frequencies, linear and nonlinear damping and nonlinear stiffness. Beyond faithfully reproducing attracting steady states and limit cycles, our SSM-reduced models can also uncover hidden motion not seen in the video, such as unstable fixed points and unstable limit cycles forming basin boundaries. We demonstrate all these features on experimental videos of five physical systems: a double pendulum, an inverted flag in counter-flow, water sloshing in tank, a wing exhibiting aeroelastic flutter and a shimmying wheel.
format Preprint
id arxiv_https___arxiv_org_abs_2406_08893
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Modeling Nonlinear Dynamics from Videos
Yang, Antony
Axås, Joar
Kádár, Fanni
Stépán, Gábor
Haller, George
Dynamical Systems
We introduce a method for constructing reduced-order models directly from videos of dynamical systems. The method uses a non-intrusive tracking to isolate the motion of a user-selected part in the video of an autonomous dynamical system. In the space of delayed observations of this motion, we reconstruct a low-dimensional attracting spectral submanifold (SSM) whose internal dynamics serves as a mathematically justified reduced-order model for nearby motions of the full system. We obtain this model in a simple polynomial form that allows explicit identification of important physical system parameters, such as natural frequencies, linear and nonlinear damping and nonlinear stiffness. Beyond faithfully reproducing attracting steady states and limit cycles, our SSM-reduced models can also uncover hidden motion not seen in the video, such as unstable fixed points and unstable limit cycles forming basin boundaries. We demonstrate all these features on experimental videos of five physical systems: a double pendulum, an inverted flag in counter-flow, water sloshing in tank, a wing exhibiting aeroelastic flutter and a shimmying wheel.
title Modeling Nonlinear Dynamics from Videos
topic Dynamical Systems
url https://arxiv.org/abs/2406.08893