We propose a method for model reduction on a given frequency range, without the use of input and output filter weights. The method uses a nonlinear optimization approach to minimize a frequency limited H2 like cost function. An important contribution in the paper is the derivation of the gradient of the proposed cost function. The fact that we have a closed form expression for the gradient and that considerations have been taken to make the gradient computationally efficient to compute enables us to efficiently use off-the-shelf optimization software to solve the optimization problem.
Cite
@article{arxiv.1212.1603,
title = {Model Reduction using a Frequency-Limited H2-Cost},
author = {Daniel Petersson and Johan Löfberg},
journal= {arXiv preprint arXiv:1212.1603},
year = {2012}
}