Cart (Loading....) | Create Account
Close category search window
 

Robust Fault Diagnosis Based on Nonlinear Model of Hydraulic Gauge Control System on Rolling Mill

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)
Min Dong ; Coll. of Mech. Eng., Yanshan Univ., Qinhuangdao, China ; Cai Liu ; Guoyou Li

A nonlinear model of a hydraulic automatic gauge control (AGC) system is established for fault detection and isolation (FDI). By analyzing the relationship between faults and load uncertainties, a decoupling subsystem has been derived using a differential geometric approach. An exponential gain observer has been designed based on the observable decoupling subsystem. Diagnosis residual signal is sensitive to designated faults and robust to load uncertainty. Two real data examples verify that the observer is stable and asymptotically convergent. The correctness and superiority are testified by actual data examples.

Published in:

Control Systems Technology, IEEE Transactions on  (Volume:18 ,  Issue: 2 )

Date of Publication:

March 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.