A new model order reduction (MOR) method for large-scale time-delay differential algebra systems is proposed herein. The presented MOR algorithm is based on parametric moment matching and $$\varepsilon $$ -embedding. By selecting an appropriate projection matrix, this process generates reduced-order models that preserve the structure of the original time-delay differential algebra system. Additionally, moment-matching results and error estimations are provided. Finally, two numerical circuits are tested to illustrate the effectiveness of the proposed MOR method.

中文翻译：

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$$\varepsilon $$-时滞微分代数系统的嵌入模型约简方法

本文提出了一种新的用于大规模时滞微分代数系统的模型降阶(MOR)方法。提出的 MOR 算法基于参数矩匹配和 $$\varepsilon $$ -embedding。通过选择合适的投影矩阵，该过程生成降阶模型，保留原始时滞微分代数系统的结构。此外，还提供了力矩匹配结果和误差估计。最后，测试了两个数值电路以说明所提出的 MOR 方法的有效性。