Model reduction of nonlinear time-delay systems via ODE approximation and spectral submanifolds

TL;DR

This paper introduces a model reduction method for nonlinear time-delay systems by approximating them as ODEs and using spectral submanifolds to create efficient reduced-order models that capture complex dynamics.

Contribution

The authors develop a novel framework combining ODE approximation and spectral submanifolds for reducing nonlinear time-delay systems, enabling accurate and efficient analysis.

Findings

ROMs predict nonlinear behaviors including vibrations and bifurcations

Spectral submanifolds accurately identify response curve features

Method demonstrated on increasingly complex examples

Abstract

Time-delay dynamical systems inherently embody infinite-dimensional dynamics, thereby amplifying their complexity. This aspect is especially notable in nonlinear dynamical systems, which frequently defy analytical solutions and necessitate approximations or numerical methods. These requirements present considerable challenges for the real-time simulation and analysis of their nonlinear dynamics. To address these challenges, we present a model reduction framework for nonlinear time-delay systems using spectral submanifolds (SSMs). We first approximate the time-delay systems as ordinary differential equations (ODEs) without delay and then compute the SSMs and their associated reduced-order models (ROMs) of the ODE approximations. These SSM-based ROMs successfully predict the nonlinear dynamical behaviors of the time-delay systems, including free and forced vibrations, and accurately identify critical features such as isolated branches in the forced response curves and bifurcations of periodic and quasi-periodic orbits. The efficiency and accuracy of the ROMs are demonstrated through examples of increasing complexity.