@Article{CiCP-12-1520,
author = {Alex Solomonoff},
title = {System Reduction Using an LQR-Inspired Version of Optimal Replacement Variables},
journal = {Communications in Computational Physics},
year = {2012},
volume = {12},
number = {5},
pages = {1520--1540},
abstract = {<p style="text-align: justify;">Optimal Replacement Variables (ORV) is a method for approximating a large
system of ODEs by one with fewer equations, while attempting to preserve the essential dynamics of a reduced set of variables of interest. An earlier version of ORV [1]
had some issues, including limited accuracy and in some rare cases, instability. Here
we present a new version of ORV, inspired by the linear quadratic regulator problem of
control theory, which provides better accuracy, a guarantee of stability and is in some
ways easier to use.</p>},
issn = {1991-7120},
doi = {https://doi.org/10.4208/cicp.190311.270112a},
url = {http://global-sci.org/intro/article_detail/cicp/7345.html}
}