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<p>This paper discusses the predictive capability of Dynamic Mode Decomposition (DMD) in the context of orbital mechanics. The focus is specifically on the Hankel variant of DMD which uses a stacked set of time-delayed observations for system identification and subsequent prediction. A theory on the minimum number of time delays required for accurate reconstruction of periodic trajectories of nonlinear systems is presented and corroborated using experimental analysis. In addition, the window size for training and prediction regions, respectively, is presented. The need for a meticulous approach while using DMD is emphasized by comparing its performance on two candidate satellites, the ISS and MOLNIYA-3-50. Experiments are also presented for quasi-periodic scenarios with applied perturbing forces.</p>

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On the Predictive Capability of Dynamic Mode Decomposition for Periodic Solutions of Nonlinear Systems with Focus on Orbital Mechanics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月19日

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  • Sriram Narayanan,
  • Mohamed Naveed Gul Mohamed,
  • Indranil Nayak,
  • Suman Chakravorty,
  • Mrinal Kumar

摘要

This paper discusses the predictive capability of Dynamic Mode Decomposition (DMD) in the context of orbital mechanics. The focus is specifically on the Hankel variant of DMD which uses a stacked set of time-delayed observations for system identification and subsequent prediction. A theory on the minimum number of time delays required for accurate reconstruction of periodic trajectories of nonlinear systems is presented and corroborated using experimental analysis. In addition, the window size for training and prediction regions, respectively, is presented. The need for a meticulous approach while using DMD is emphasized by comparing its performance on two candidate satellites, the ISS and MOLNIYA-3-50. Experiments are also presented for quasi-periodic scenarios with applied perturbing forces.