Open AccessIdentification of Nonlinear Systems Structured by Wiener-Hammerstein Model
Author(s) -
Adil Brouri,
Smail Slassi
Publication year - 2016
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v6i1.pp167-176
Subject(s) - invertible matrix , nonlinear system , identification (biology) , series (stratigraphy) , nonlinear element , simple (philosophy) , mathematics , computer science , system identification , control theory (sociology) , connection (principal bundle) , nonparametric statistics , nonlinear system identification , mathematical optimization , artificial intelligence , econometrics , physics , data modeling , pure mathematics , paleontology , philosophy , database , botany , control (management) , geometry , epistemology , quantum mechanics , biology
Wiener-Hammerstein systems consist of a series connection including a nonlinear static element sandwiched with two linear subsystems. The problem of identifying Wiener-Hammerstein models is addressed in the presence of hard nonlinearity and two linear subsystems of structure entirely unknown (asymptotically stable). Furthermore, the static nonlinearity is not required to be invertible. Given the system nonparametric nature, the identification problem is presently dealt with by developing a two-stage frequency identification method, involving simple inputs.