System identification of simplified crash models using multi-objective optimization

Authors
Marler, RTKim, CHArora, JS
Issue Date
2006-07
Publisher
ELSEVIER SCIENCE SA
Citation
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, v.195, no.33-36, pp.4383 - 4395
Abstract
A multi-objective optimization (MOO) based methodology is presented to identify simplified dynamic system simulation models. The proposed methodology is used to develop a three degree-of-freedom model for an automotive crash simulation. To date, such system identification problems have only been approached as single-objective problems. We use various MOO methods to provide new insight into the problem. Furthermore, we use this problem to study the nature of the Pareto optimal hypersurface, normalization of objectives, and specification of preferences. In general, we find that the MOO-based methodology is quite useful for dynamic system identification problems. (c) 2005 Elsevier B.V. All rights reserved.
Keywords
NONPARAMETRIC IDENTIFICATION; NONPARAMETRIC IDENTIFICATION; optimization; multi-objective; crash models; dynamic system identification
ISSN
0045-7825
URI
https://pubs.kist.re.kr/handle/201004/135357
DOI
10.1016/j.cma.2005.09.002
Appears in Collections:
KIST Article > 2006
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