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<p>The extended dynamic mode decomposition framework provides a data-driven way to approximate a finite-dimension nonlinear dynamic system with control inputs in Euclidean space as a bilinear system. In this paper, we present a novel data-driven method for dynamic modeling of constrained mechanisms with control inputs, using bilinear models on manifolds. The proposed method not only achieves high accuracy in dynamic predictions but also strictly maintains position and velocity constraints. We demonstrate the effectiveness of the proposed method through three numerical examples.</p>

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Data-driven bilinear models on manifolds for dynamic modeling of constrained mechanisms

  • 期刊论文

  • 发表日期：

    2025年5月8日

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  • Haocheng Ying,
  • Ye Ding

摘要

The extended dynamic mode decomposition framework provides a data-driven way to approximate a finite-dimension nonlinear dynamic system with control inputs in Euclidean space as a bilinear system. In this paper, we present a novel data-driven method for dynamic modeling of constrained mechanisms with control inputs, using bilinear models on manifolds. The proposed method not only achieves high accuracy in dynamic predictions but also strictly maintains position and velocity constraints. We demonstrate the effectiveness of the proposed method through three numerical examples.