Asian Journal of Information Technology
ISSN: Online 1993-5994ISSN: Print 1682-3915
Abstract
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.
How to cite this article:
Mehennaoui, L. , N. Debbache and M.L. Benlouci . Neuro Fuzzy Methods for Fault Diagnosis of Nonlinear Systems.
DOI: https://doi.org/10.36478/ajit.2006.750.760
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2006.750.760