求解非线性微分-代数方程组的一种算法,即使在高要求精度下也具有非凡的效率

J. Dobes, D. Cerny
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引用次数: 1

摘要

在许多情况下,非线性微分代数方程组需要非常精确地求解。稳态分析(确定系统暂态后的稳态周期)是一个典型的例子,因为在长周期区间上进行数值积分后,未知变量向量应该完全相同。因此,我们需要开发这样一种计算有效的数值算法,即使对结果的准确性要求很高。本文首先描述了求解代数-微分非线性方程组的一种高效可靠的算法。不像在其他情况下,程序是基于一个复杂的安排牛顿插值多项式(即,不是拉格朗日一个)。该功能在数值积分过程中快速变化的插补步长和顺序提供了更大的灵活性。文中最后给出了两个复杂的算例,说明该算法的计算量很低,即使对结果的精度要求很高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Algorithm to Solve Systems of Nonlinear Differential-Algebraic Equations With Extraordinary Efficiency Even at High Demanded Precisions
There are many situations when systems of non-linear differential algebraic equations need to be solved with extraordinary precision. A steady-state analysis (determining the steady-state period of a system after a transient) is a typical case because a vector of unknown variables should be exactly the same after a numerical integration on the period-long interval. Therefore, we need to develop such kinds of numerical algorithms that are computationally effective, even at very high requirements on the accuracy of the results. In the paper, an efficient and reliable algorithm for solving systems of algebraic-differential nonlinear equations is characterized first. Unlike in other cases, the procedure is based on a sophisticated arrangement of the Newton interpolation polynomial (i.e., not the Lagrange one). This feature provides greater flexibility in rapidly changing interpolation step sizes and orders during numerical integration. At the end of the paper, two complicated examples are presented to demonstrate that the algorithm’s computational requirement is quite low, even at very high demands on the accuracy of results.
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