ICGST- ACSE Journal

ACSE Volume (9) - Issue (II) ICGST

Greenhouse Model Identification based on Fuzzy Clustering Approach

 A. Errahmani*, M. Benyakhlef** and I. Boumhidi*

* LESSI, Départment de physique, Faculté des Sciences Dhar El Mehraz.
BP 1796 Atlas Fez 30 000 MOROCCO
** Faculté Poly disciplinaire Taza

Abstract
Fuzzy modelling has been widely applied as a powerful methodology for the identification of nonlinear system from process measurements. This work proposes a contribution on the application of fuzzy logic to identification of a class of large scale system with multiple models. The researched models have black box structure and the rules are determined by numerical approaches. The proposed approach is developed by using fuzzy clustering and is applied on a real system which is nonlinear in nature (greenhouse).

Keywords: Identification of nonlinear systems, Fuzzy clustering, greenhouse climate modelling.

(P1110917728, 830 KB)

@ARTICLE{P1110917728,

AUTHOR = {A. Errahmani and M. Benyakhlef and I. Boumhidi},
 
TITLE = {Greenhouse Model Identification based on Fuzzy Clustering Approach},

JOURNAL = {ICGST International Journal on Automatic Control and Systems Engineering, ACSE},

YEAR = {2009},

VOLUME = {09},

ISSUE = {II},

PAGES={23--27}

}

(P1110917728, 830 KB)