Model order reduction via time moment modeling and clustering technique

A high order dynamic system can be reduced by a technology reduces the system through improved pole clustering and pade approximations. In this method the characteristics and property of actual and new reduced systems are remain unchanged. For numerator coefficient pade approximations and for denominator coefficient pole clustering method is used. By comparing the proposed method with existing method it shows that the anticipated method guarantees the immovability of the reduced model and it has some advantages also i.e. calculation straightforwardness, and immovability retention etc. The dominance of the anticipated method is shown through literary examples.