A Hybrid Approach for Simplification Using Logarithmic Clustering and Moments Matching

Abstract

A simplification method is suggested in this paper to simplify a large-scale dynamic system using logarithmic pole clustering and moments matching using Pade approximations. The denominator polynomial of the simplified model is computed by using logarithmic pole clustering while the numerator coefficients of the same model are determined by matching the time-moments of the original large-scale system. The viability of the proposed method has been tested on few large-scale systems taken from the literature.