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

被引：0
|
作者：
Bouabdallah, Salma Bouslama [1 ]
Tagina, Moncef [2 ]
机构：
[1] Ecole Natl Ingenieurs Tunis, LACS, Campus Univ,BP 37, Tunis 1002, Tunisia
[2] Ecole Natl Sci Informat, Manouba 2010, Tunisia
来源：
INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL | 2010年 / 4卷 / 01期
关键词：
bond graph; Fault Detection and Isolation; FDI; fuzzy logic; multilayer perceptron; systems with parameter uncertainties;
D O I：
10.1504/IJAAC.2010.029842
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：102 / 126
页数：25
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