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A coordinate-transformed Arnoldi algorithm for generating guaranteed stable reduced-order models of RLC circuits

机译:用于生成保证稳定的RLC电路降阶模型的坐标变换Arnoldi算法

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摘要

Since the first papers on asymptotic waveform evaluation (AWE), Pade-based reduced order models have become standard for improving coupled circuit-interconnect simulation efficiency. Such models can be accurately computed using bi-orthogonalization algorithms like Pade via Lanczos (PVL), but the resulting Pade approximates can still be unstable even when generated from stable RLC circuits. For certain classes of RC circuits it has been shown that congruence transforms, like the Arnoldi algorithm, can generate guaranteed stable and passive reduced-order models. In this paper we present a computationally efficient model-order reduction technique, the coordinate-transformed Arnoldi algorithm, and show that this method generates arbitrarily accurate and guaranteed stable reduced-order models for RLC circuits. Examples are presented which demonstrates the enhanced stability and efficiency of the new method.
机译:从关于渐近波形评估(AWE)的第一篇论文开始,基于Pade的降阶模型已成为提高耦合电路互连仿真效率的标准。可以使用双向正交算法(如Pade via Lanczos(PVL))来精确计算此类模型,但是即使从稳定的RLC电路生成的结果,Pade近似值仍可能不稳定。对于某些类型的RC电路,已经证明,同余变换(如Arnoldi算法)可以生成有保证的稳定和无源降阶模型。在本文中,我们提出了一种计算效率高的模型降阶技术,即坐标变换的Arnoldi算法,并表明该方法为RLC电路生成了任意准确且有保证的稳定降阶模型。举例说明了新方法的增强的稳定性和效率。

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