提出新型非线性机械系统建模方法，提升鲁棒性与计算效率。
Efficient and Robust Modeling of Nonlinear Mechanical Systems
- 基于新公式自动推导模型，适用于汽车与机器人场景。
- 相比欧拉-拉格朗日法，抗噪声能力更强，逆动力学计算更快。
- 适合需要高精度与实时性的机械系统建模任务。
高效且稳健的动力学建模在系统与控制工程中至关重要。本文提出一种新型非线性机械系统动力学模型的表述方式，并配套开发了自动获取模型表达式的建模流程，可应用于不同汽车与机器人案例。与欧拉-拉格朗日方法相比，该方法在依赖外部变量的系统中表现出更强的抗测量噪声能力，同时在计算系统逆动力学时具有更优的执行效率。
原文摘要 · Abstract (English)
The development of efficient and robust dynamic models is fundamental in the field of systems and control engineering. In this paper, a new formulation for the dynamic model of nonlinear mechanical systems, that can be applied to different automotive and robotic case studies, is proposed, together with a modeling procedure allowing to automatically obtain the model formulation. Compared with the Euler-Lagrange formulation, the proposed model is shown to give superior performances in terms of robustness against measurement noise for systems exhibiting dependence on some external variables, as well as in terms of execution time when computing the inverse dynamics of the system.
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