Efficient Model Order Reduction Research Articles

A New Methodology for the Transient Analysis of Lossy and Dispersive Multiconductor Transmission Lines

This paper presents a new technique for the transient analysis of multiconductor transmission lines (MTLs). The proposed model is derived from the analytical characterization of half-T ladder networks (HTLNs), which approximate the MTLs. Using closed-form polynomials (named D'Amico-Faccio-Ferri (DFF) and DFFz), poles and residues of the two-port representation of MTLs are extracted analytically, thus leading to a time-domain macromodel, which can be incorporated in a circuit simulator. Furthermore, the knowledge of poles allows one to develop an efficient model order reduction technique by selecting only the dominant poles of the system within a fixed bandwidth. Stability and passivity properties of the proposed model are intrinsically enforced as a consequence of stability and passivity of HTLNs and rational approximation procedure.

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

Since the first papers on asymptotic waveform evaluation (AWE), Padé-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 Padé via Lanczos (PVL), but the resulting Padé 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.