Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

A neural network approach to robust model-based diagnosis of faults in a three-tank system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Marcu, T. ; Dept. of Autom. Control & Ind. Inf., Tech. Univl of Iasi, Romania ; Mirea, L. ; Klosz, A.

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

Published in:

Computer-Aided Control System Design, 1996., Proceedings of the 1996 IEEE International Symposium on

Date of Conference:

15-18 Sep 1996