Abstract
ABSTRACTThis paper presents a method for the reduction of higher order linear discrete time system into a desired reduced order model. The proposed algorithm uses the concept of pattern recognition which is adopted here for clustering the poles of the system. The centres of the clusters are treated as poles of the reduced order model and the overall transfer function of the reduced order model is obtained by both clustering algorithm and matching the ratio of coefficients of original and reduced order models. The original algorithm for c-means clustering is modified in order to avoid some limitations in model order reduction procedure. This new method makes the procedure simple, in addition to retaining the stability of the original higher order system in their reduced order models.
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