Model Reduction by Rational Interpolation
Numerical Analysis
2014-09-18 v1 Numerical Analysis
Systems and Control
Abstract
The last two decades have seen major developments in interpolatory methods for model reduction of large-scale linear dynamical systems. Advances of note include the ability to produce (locally) optimal reduced models at modest cost; refined methods for deriving interpolatory reduced models directly from input/output measurements; and extensions for the reduction of parametrized systems. This chapter offers a survey of interpolatory model reduction methods starting from basic principles and ranging up through recent developments that include weighted model reduction and structure-preserving methods based on generalized coprime representations. Our discussion is supported by an assortment of numerical examples.
Cite
@article{arxiv.1409.2140,
title = {Model Reduction by Rational Interpolation},
author = {Christopher Beattie and Serkan Gugercin},
journal= {arXiv preprint arXiv:1409.2140},
year = {2014}
}