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arXiv 1407.2116math.NAcs.NAmath-phmath.DSmath.MP
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关于$\mathbb{R}^n$中非完整动力学离散化的研究

On the discretization of nonholonomic dynamics in $\mathbb{R}^n$

Technische Universität München(慕尼黑工业大学)

Fernando Jimenez, Juergen Scheurle

AI总结:

本文探讨了机械系统在有限维配置流形局部坐标下的非完整Lagrangian设定,通过将运动基本方程转化为分布流形$D$上的常微分方程,证明了解的存在性和唯一性,并构建了保持分布$D$的几何积分器。

摘要:

本文探讨了机械系统在有限维配置流形局部坐标下的非完整Lagrangian设定。我们通过将运动基本方程转化为分布流形$D$上的常微分方程,证明了解的存在性和唯一性。此外,我们证明任何保持$D$的离散化均可视为由原非完整系统的时变扰动的精确演化映射生成。通过离散化相应的Lagrange-d'Alembert原理,我们构建了原非完整系统的几何积分器,并给出了这些积分器生成保持分布$D$的离散流的精确条件。我们还推导了相应的收敛估计。最后,我们详细处理了非完整粒子的例子,展示了如何合理离散化运动方程,特别是关于非完整约束的问题。本文的研究为分析适当非完整机械系统离散化的Lagrangian动力学及将其与原非完整系统动力学相关联奠定了基础。我们推迟此分析至后续系列论文中。

英文摘要:

In this paper we explore the nonholonomic Lagrangian setting of mechanical systems in local coordinates on finite-dimensional configuration manifolds. We prove existence and uniqueness of solutions by reducing the basic equations of motion to a set of ordinary differential equations on the underlying distribution manifold $D$. Moreover, we show that any $D-$preserving discretization may be understood as beeing generated by the exact evolution map of a time-periodic non-autonomous perturbation of the original continuous-time nonholonomic system. By means of discretizing the corresponding Lagrange-d'Alembert principle, we construct geometric integrators for the original nonholonomic system. We give precise conditions under which these integrators generate a discrete flow preserving the distribution $D$. Also, we derive corresponding consistency estimates. Finally, we carefully treat the example of the nonholonomic particle, showing how to discretize the equations of motion in a reasonable way, particularly regarding the nonholonomic constraints. The exploration in this paper lays the ground to analyze the dynamics of appropriate discretizations of nonholonomic mechnical systems in the Lagrangian framework and to relate that dynamics to the dynamics of the original nonholonomic systems. We postpone this analysis to a series of forthcoming papers.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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