ABCD-L: Approximating continuous linear systems using Boolean models

Aadithya V. Karthik, J. Roychowdhury
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引用次数: 19

Abstract

In this supplement, we provide additional context for ABCD-L and place our contributions in perspective, relative to the existing body of literature on topics like AMS modelling/verification, Boolean and hybrid systems frameworks, etc. Further, we demonstrate that ABCD-L can be applied in conjunction with Model Order Reduction (MOR) techniques, to Booleanize large LTI systems whose direct eigendecomposition may be computationally infeasible. For example, we combine ABCD-L with Arnoldi iteration based MOR to efficiently produce accurate Boolean models of a real-world power grid network (with 25849 nodes) obtained from a benchmark set made available by IBM. Due to space constraints, we were unable to include such material within our main manuscript.
用布尔模型逼近连续线性系统
在本增刊中,我们为ABCD-L提供了额外的背景,并将我们的贡献与AMS建模/验证、布尔和混合系统框架等主题的现有文献相比较。此外,我们证明ABCD-L可以与模型阶降阶(MOR)技术结合应用,以布尔化大型LTI系统,其直接特征分解可能在计算上不可行。例如,我们将ABCD-L与基于Arnoldi迭代的MOR相结合,以有效地生成从IBM提供的基准集获得的真实电网网络(具有25849个节点)的精确布尔模型。由于篇幅限制,我们无法将这些材料包括在我们的主要手稿中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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