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引用次数: 0
摘要
本文重点讨论耦合系统的模型阶次缩减(MOR)问题。首先,本文提出了一种通过拉盖尔多项式展开对此类系统的可控性和可观测性格兰进行近似的方法,它提供了一种低阶分解形式,其因子由递推公式而非 Lyapunov 方程构建。然后,结合平衡截断法和优势子空间投影法,提出了一系列保留耦合结构的 MOR 算法。此外,还充分讨论了减阶模型的一些主要特性,如稳定性保持等。最后,我们提供了三个数值模拟来说明我们算法的有效性。
Dimension reduction based on approximate gramians via Laguerre polynomials for coupled systems
In this paper, we focus on the topic of model order reduction (MOR) for coupled systems. At first, an approximation via Laguerre polynomials expansions to controllability and observability gramians for such systems are presented, which provides a low-rank decomposition form whose factors are constructed from a recurrence formula instead of Lyapunov equations. Then, in combination of balanced truncation and dominant subspace projection method, a series of MOR algorithms are proposed that preserve the coupled structures. What’s more, some main properties of reduced-order models, such as stability preservation, are well discussed. Finally, three numerical simulations are provided to illustrate the effectiveness of our algorithms.
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