Title :
A neural network approach to robust model-based diagnosis of faults in a three-tank system
Author :
Marcu, Teodor ; Mirea, Letitia ; Klósz, Attila
Author_Institution :
Dept. of Autom. Control & Ind. Inf., Tech. Univl of Iasi, Romania
Abstract :
The problem of robust model-based diagnosis of faults is addressed with application to a three-tank system. The present approach is based on artificial neural networks used as predictors of dynamic nonlinear models for residual generation, and as pattern classifiers for residual evaluation. A diagnosing subsystem is implemented in real-time using the Simulink/Matlab environment
Keywords :
fault diagnosis; multilayer perceptrons; nonlinear dynamical systems; parameter estimation; pattern classification; process control; Matlab; Simulink; dynamic nonlinear models; identification; model-based fault diagnosis; multilayer perceptron; neural network; nonlinear systems; parameter estimation; pattern classification; real-time systems; residual generation; three-tank system; Artificial neural networks; Autoregressive processes; Fault diagnosis; Intelligent networks; Neural networks; Nonlinear dynamical systems; Pattern recognition; Predictive models; Robustness; Signal generators;
Conference_Titel :
Computer-Aided Control System Design, 1996., Proceedings of the 1996 IEEE International Symposium on
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-3032-3
DOI :
10.1109/CACSD.1996.555240
