TY  - JOUR
JF  - Journal of Electronic Testing: Theory and Applications (JETTA)
EP  - 877
SP  - 861
N2  - 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.
A1  - Xia, L.
A1  - Farooq, M.U.
A1  - Bell, I.M.
A1  - Hussin, F.A.
A1  - Malik, A.S.
N1  - cited By 2
Y1  - 2013///
SN  - 09238174
VL  - 29
TI  - Survey and evaluation of automated model generation techniques for high level modeling and high level fault modeling
AV  - none
ID  - scholars3329
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891630810&doi=10.1007%2fs10836-013-5401-0&partnerID=40&md5=b6809552a6ec934a532b0dc1199dff8f
KW  - Advanced researches; Automated model generations; High-level fault models; High-level modeling; Model order reduction; Nonlinear behavior; Strongly nonlinear system
KW  -  Automation; Linear systems; Nonlinear systems
KW  -  Surveys
IS  - 6
ER  -