Improved Reduced-Order Modeling Using Clustering Method with Dominant Pole Retention

Abstract

This paper provides a quantitative measure criterion for selection of poles from a higher order model. The selection of poles is important because it determines both the transient and steady-state information of the dynamical system. The new indices specify which poles are dominant even when they are not the slowest. On the basis of important poles contribution to the system poles, they are selected to form cluster center. Pade approximation method is used to estimate the coefficients of numerator polynomial. Besides, this technique gives a better approximation in both the transient and the steady-state responses of the large-scale system. The effectiveness of the proposed method is demonstrated through numerical test examples and compared with other well-known published methods.