Title: Application of artificial intelligence in Fault Detection and Isolation of uncertain parameter systems

Authors: Salma Bouslama Bouabdallah, Moncef Tagina

Addresses: LACS, Ecole Nationale d'Ingenieurs de Tunis, Campus universitaire, BP 37, 1002 Tunis, Tunisie. ' Ecole Nationale des Sciences de l'Informatique, Campus Universitaire, 2010 Manouba, Tunisie

Abstract: In this article, two original intelligent methods for Fault Detection and Isolation (FDI) affecting sensors and actuators in case of bond graph modelled uncertain parameter systems are proposed. First, a fuzzy approach based on residual processing is proposed for FDI offline, binary approach and fuzzy approach are compared through an illustrative example. Secondly, a multilayer perceptron trained with resilient backpropagation algorithm is proposed for FDI online.

Keywords: bond graphs; fault detection; fault isolation; FDI; fuzzy logic; multilayer perceptron; parameter uncertainties; artificial intelligence; artificial neural networks.

DOI: 10.1504/IJAAC.2010.029842

International Journal of Automation and Control, 2010 Vol.4 No.1, pp.102 - 126

Received: 26 Oct 2007
Accepted: 05 Feb 2008
Published online: 02 Dec 2009 *

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