Data-Driven Nonlinear Model Reduction to Spectral Submanifolds via Oblique Projection

Fuente: arXiv
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Autori principali: Bettini, Leonardo, Kaszás, Bálint, Zybach, Bernhard, Dual, Jürg, Haller, George
Natura: Preprint
Pubblicazione: 2025
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author Bettini, Leonardo
Kaszás, Bálint
Zybach, Bernhard
Dual, Jürg
Haller, George
author_facet Bettini, Leonardo
Kaszás, Bálint
Zybach, Bernhard
Dual, Jürg
Haller, George
contents The dynamics in a primary Spectral Submanifold (SSM) constructed over the slowest modes of a dynamical system provide an ideal reduced-order model for nearby trajectories. Modeling the dynamics of trajectories further away from the primary SSM, however, is difficult if the linear part of the system exhibits strong non-normal behavior. Such non-normality implies that simply projecting trajectories onto SSMs along directions normal to the slow linear modes will not pair those trajectories correctly with their reduced counterparts on the SSMs. In principle, a well-defined nonlinear projection along a stable invariant foliation exists and would exactly match the full dynamics to the SSM-reduced dynamics. This foliation, however, cannot realistically be constructed from practically feasible amounts and distributions of experimental data. Here we develop an oblique projection technique that is able to approximate this foliation efficiently, even from a single experimental trajectory of a significantly non-normal and nonlinear beam.
format Preprint
id arxiv_https___arxiv_org_abs_2503_21895
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Data-Driven Nonlinear Model Reduction to Spectral Submanifolds via Oblique Projection
Bettini, Leonardo
Kaszás, Bálint
Zybach, Bernhard
Dual, Jürg
Haller, George
Dynamical Systems
Computational Engineering, Finance, and Science
Systems and Control
Differential Geometry
Optimization and Control
The dynamics in a primary Spectral Submanifold (SSM) constructed over the slowest modes of a dynamical system provide an ideal reduced-order model for nearby trajectories. Modeling the dynamics of trajectories further away from the primary SSM, however, is difficult if the linear part of the system exhibits strong non-normal behavior. Such non-normality implies that simply projecting trajectories onto SSMs along directions normal to the slow linear modes will not pair those trajectories correctly with their reduced counterparts on the SSMs. In principle, a well-defined nonlinear projection along a stable invariant foliation exists and would exactly match the full dynamics to the SSM-reduced dynamics. This foliation, however, cannot realistically be constructed from practically feasible amounts and distributions of experimental data. Here we develop an oblique projection technique that is able to approximate this foliation efficiently, even from a single experimental trajectory of a significantly non-normal and nonlinear beam.
title Data-Driven Nonlinear Model Reduction to Spectral Submanifolds via Oblique Projection
topic Dynamical Systems
Computational Engineering, Finance, and Science
Systems and Control
Differential Geometry
Optimization and Control
url https://arxiv.org/abs/2503.21895