eprintid: 3329
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/33/29
datestamp: 2023-11-09 15:51:35
lastmod: 2023-11-09 15:51:35
status_changed: 2023-11-09 15:46:35
type: article
metadata_visibility: show
creators_name: Xia, L.
creators_name: Farooq, M.U.
creators_name: Bell, I.M.
creators_name: Hussin, F.A.
creators_name: Malik, A.S.
title: Survey and evaluation of automated model generation techniques for high level modeling and high level fault modeling
ispublished: pub
keywords: Advanced researches; Automated model generations; High-level fault models; High-level modeling; Model order reduction; Nonlinear behavior; Strongly nonlinear system, Automation; Linear systems; Nonlinear systems, Surveys
note: cited By 2
abstract: It is known that automated model generation (AMG) techniques for linear systems are sufficiently mature to handle linear systems during high level modeling (HLM). Other AMG techniques have been developed for various levels of nonlinear behavior and to focus on specific issues such as high level fault modeling (HLFM). However, no single nonlinear AMG technique exists which can be confidently adapted for any nonlinear system. In this paper, a survey on AMG techniques over the last two decades is conducted. The techniques are classified into two main areas: system identification (SI) based AMG and model order reduction (MOR) based AMG. Overall, the survey reveals that more advanced research for AMG techniques is required to handle strongly nonlinear systems during HLFM. © 2013 Springer Science+Business Media New York.
date: 2013
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891630810&doi=10.1007%2fs10836-013-5401-0&partnerID=40&md5=b6809552a6ec934a532b0dc1199dff8f
id_number: 10.1007/s10836-013-5401-0
full_text_status: none
publication: Journal of Electronic Testing: Theory and Applications (JETTA)
volume: 29
number: 6
pagerange: 861-877
refereed: TRUE
issn: 09238174
citation:   Xia, L. and Farooq, M.U. and Bell, I.M. and Hussin, F.A. and Malik, A.S.  (2013) Survey and evaluation of automated model generation techniques for high level modeling and high level fault modeling.  Journal of Electronic Testing: Theory and Applications (JETTA), 29 (6).  pp. 861-877.  ISSN 09238174