Vector Fitting
Abstract
We introduce the Vector Fitting algorithm for the creation of reduced-order models from the sampled response of a linear time-invariant system. This data-driven approach to reduction is particularly useful when the system under modeling is known only through experimental measurements. The theory behind Vector Fitting is presented for single- and multiple-input systems, together with numerical details, pseudocodes, and an open-source implementation. We discuss how the reduced model can be made stable and converted to a variety of forms for use in virtually any modeling context. Finally, we survey recent extensions of the Vector Fitting algorithm geared towards time-domain, parametric and distributed systems modeling.
Cite
@article{arxiv.1908.08977,
title = {Vector Fitting},
author = {Piero Triverio},
journal= {arXiv preprint arXiv:1908.08977},
year = {2019}
}
Comments
This work is a draft of the book chapter P. Triverio, "Vector Fitting" that will be part of the "Handbook on Model Order Reduction" edited by P. Benner, S. Grivet-Talocia, A. Quarteroni, G. Rozza, W. H. A. Schilders, L. M. Silveira, to appear for De Gruyter