Model Order Reduction via Moment-Matching: A State of the Art Review

The past few decades have seen a significant spurt in developing lower-order, parsimonious models of large-scale dynamical systems used for design and control. These surrogate models effectively capture the most interesting dynamic features of the full-order models (FOMs) while preserving the input–...

Full description

Saved in:
Bibliographic Details
Published in:Archives of computational methods in engineering 2022-05, Vol.29 (3), p.1463-1483
Main Authors: Rafiq, Danish, Bazaz, Mohammad Abid
Format: Article
Language:English
Subjects:
Dynamical systems
Engineering
Matching
Mathematical and Computational Engineering
Microelectromechanical systems
Model reduction
Nonlinear systems
Review Article
State-of-the-art reviews
System effectiveness
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The past few decades have seen a significant spurt in developing lower-order, parsimonious models of large-scale dynamical systems used for design and control. These surrogate models effectively capture the most interesting dynamic features of the full-order models (FOMs) while preserving the input–output relation. Model order reduction (MOR) techniques have intensively been further developed to treat increasingly complex, multi-resolution models spanning a thousand degrees of freedom. This manuscript presents a state-of-the-art review of the moment-matching based order reduction methods for linear and nonlinear dynamical systems. We track the progress of moment-matching methods from their inception to how they have emerged as the most commonly adopted platform for reducing systems in large-scale settings. We discuss the frequency and time-domain notions of moment-matching between the original and reduced models. Moreover, we also provide some new results highlighting the extensive applications of this technique in reducing micro-electro-mechanical systems.
ISSN:1134-3060
1886-1784
DOI:10.1007/s11831-021-09618-2