An algorithm for direct identification of passive transfer matrices with positive real fractions via convex programming

Abstract

Abstract The paper presents a new algorithm for the identification of a positive real rational transfer matrix of a multi‐input–multi‐output system from frequency domain data samples. It is based on the combination of least‐squares pole identification by the Vector Fitting algorithm and residue identification based on frequency‐independent passivity constraints by convex programming. Such an approach enables the identification of a priori guaranteed passive lumped models, so avoids the passivity check and subsequent (perturbative) passivity enforcement as required by most of the other available algorithms. As a case study, the algorithm is successfully applied to the macro‐modeling of a twisted cable pair, and the results compared with a passive identification performed with an algorithm based on quadratic programming (QPpassive), highlighting the advantages of the proposed formulation. Copyright © 2010 John Wiley & Sons, Ltd.