TY  - JOUR
T1  - Neuro Fuzzy Methods for Fault Diagnosis of Nonlinear Systems
AU - , Mehennaoui, L. AU - , N. Debbache AU - , M.L. Benlouci 
JO  - Asian Journal of Information Technology
VL  - 5
IS  - 7
SP  - 750
EP  - 760
PY  - 2006
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2006.750.760
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2006.750.760
KW  - Fuzzy identification
KW  -neural identification
KW  -fault diagnosis
KW  -neuro-fuzzy scheme
AB  - The study presents a Fault Detection and Isolation (FDI) scheme with a particular emphasis placed on sensor fault diagnosis in nonlinear dynamic systems. The non-analytical FDI scheme is based on a two-step procedure. Two methods are proposed for the first step, called residual generation, one use fuzzy sets and the second neuronal network. A fuzzy neural network performs the second step, called residual evaluation. Some simulation results are given for efficiency assessment of this fault diagnosis approach.
ER  -