A new frequency-weighted balanced truncation method and an error bound

In this paper, a new frequency weighted model reduction method with an error bound is proposed. The method is a generalization of Enns's technique and yields stable models even when both input and output weightings are included. The proposed method is compared with other existing methods using numerical examples.