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Volume 12, Issue 5
System Reduction Using an LQR-Inspired Version of Optimal Replacement Variables

Alex Solomonoff

Commun. Comput. Phys., 12 (2012), pp. 1520-1540.

Published online: 2012-12

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  • Abstract

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.

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@Article{CiCP-12-1520, author = {}, 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 = {

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.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.190311.270112a}, url = {http://global-sci.org/intro/article_detail/cicp/7345.html} }
TY - JOUR T1 - System Reduction Using an LQR-Inspired Version of Optimal Replacement Variables JO - Communications in Computational Physics VL - 5 SP - 1520 EP - 1540 PY - 2012 DA - 2012/12 SN - 12 DO - http://doi.org/10.4208/cicp.190311.270112a UR - https://global-sci.org/intro/article_detail/cicp/7345.html KW - AB -

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.

Alex Solomonoff. (2020). System Reduction Using an LQR-Inspired Version of Optimal Replacement Variables. Communications in Computational Physics. 12 (5). 1520-1540. doi:10.4208/cicp.190311.270112a
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