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Model reduction of nonlinear systems
Author(s) -
Condon Marissa
Publication year - 2007
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200701084
Subject(s) - reduction (mathematics) , nonlinear system , truncation (statistics) , focus (optics) , computer science , mathematics , machine learning , physics , geometry , quantum mechanics , optics
The paper is concerned with the model reduction of nonlinear systems. Such methods are required in all branches of engineering. Often the level of detail in system models can cloud the essential behaviour and hence, methods are required to identify the behaviour of interest to the designer. In this contribution, the particular focus is on the empirical balanced truncation method of model reduction. A standard test case will illustrate the efficacies of the suggested approach. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)