Passivity-Preserving Parametric Macromodeling by Means of Scaled and Shifted State-Space Systems

Abstract

We propose a novel parametric macromodeling method for systems described by admittance and impedance representations, which depend on multiple design variables such as geometrical layout or substrate features. It is able to build accurate multivariate macromodels that are stable and passive over the entire design space. Poles and residues are parameterized indirectly. The proposed method is based on an efficient and reliable combination of rational identification, a procedure to find scaling and frequency-shifting coefficients and positive interpolation schemes. Pertinent numerical results validate the high modeling capability of the proposed parametric macromodeling technique.