Geodesic
Parameter Estimation Based Fault Detection and Isolation in Wiener and Hammerstein Systems
International Journal of Applied Mathematics and Computer Science, Tome 9 (1999) no. 3, pp. 711-735 Cet article a éte moissonné depuis la source Library of Science

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Fault detection and isolation in Wiener and Hammerstein systems via generation and processing of residual sequences is considered. We assume that some models of the unfaulty Wiener and Hammerstein systems under consideration are known. For Wiener systems, we also assume that their static nonlinear subsystems are invertible. Then, based on a serial-parallel definition of the residual error, new fault detection and isolation methods are proposed.To detect and identify all the changes in both the Wiener and Hammerstein system parameters, the sequences of residuals are processed by using linear regression methods or a neural network approach.
Keywords: fault detection, fault isolation, parameter estimation, neural networks, nonlinear system
Mots-clés : wykrywanie błędu, wyodrębnienie błędu, estymacja parametryczna, sieć neuronowa, system nieliniowy 
@article{IJAMCS_1999_9_3_a10,
     author = {Janczak, A.},
     title = {Parameter {Estimation} {Based} {Fault} {Detection} and {Isolation} in {Wiener} and {Hammerstein} {Systems}},
     journal = {International Journal of Applied Mathematics and Computer Science},
     pages = {711--735},
     year = {1999},
     volume = {9},
     number = {3},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/IJAMCS_1999_9_3_a10/}
}
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Janczak, A. Parameter Estimation Based Fault Detection and Isolation in Wiener and Hammerstein Systems. International Journal of Applied Mathematics and Computer Science, Tome 9 (1999) no. 3, pp. 711-735. http://geodesic.mathdoc.fr/item/IJAMCS_1999_9_3_a10/