Passivity-preserving model order reduction of linear time-varying macromodels

Yansong Liu, N. Wong
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Abstract

We study model order reduction (MOR) of continuous-time linear time-varying (LTV) systems. Examples include circuit or interconnect models found in VLSI marco-modeling. Specifically, a time-varying version of positive-real balanced truncation (PRBT), called LTV-PRBT, is proposed, which preserves the passivity of LTV systems for stable global simulation. Implementation details are discussed together with a brief outline of a discrete-time counterpart of LTV-PRBT. Dynamically changing state dimension is allowed for accurate modeling at the lowest possible order. Numerical examples then verify the effectiveness of the proposed approach over existing LTV MOR methods.
线性时变宏观模型的无源保持模型降阶
研究了连续时间线性时变系统的模型降阶问题。例子包括在VLSI marco建模中发现的电路或互连模型。具体而言,提出了一种时变版本的正实数平衡截断(PRBT),称为LTV-PRBT,它保留了LTV系统的无源性,以实现稳定的全局仿真。讨论了实现细节,并简要概述了LTV-PRBT的离散时间对立物。动态改变状态维度允许以尽可能低的顺序进行精确建模。数值算例验证了该方法相对于现有LTV MOR方法的有效性。
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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