Enhanced accuracy in reduced order modeling for linear stable\unstable system

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 centre. Factor division algorithm is applied to compute the coefficient of the numerator polynomial for determining denominator polynomial. This method extended for the reduction of the unstable system via additive decomposition technique. The proposed method not only can cause less dynamic errors, but also yields zero steady-state error. The efficiency and accuracy of the proposed method are demonstrated through benchmark test examples taken from the literature.