Simulation based reduced order modeling using a clustering technique

Abstract A new method for reduced order modelling based on clustering the poles and zeros of a high order scalar transfer function is presented. The poles and zeros of the original system in the s -plane are clustered using a newly defined “inverse distance measure”. The reduced order model is identified from the cluster-centres. A tuning factor k is used to minimize the cumulative square of the time response deviations between the original system and the reduced order approximant. The viability of the method is illustrated by some examples from the literature.

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