By Topic

Robust Fault Diagnosis of a Satellite System Using a Learning Strategy and Second Order Sliding Mode Observer

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

2 Author(s)
Qing Wu ; Sch. of Eng. Sci., Simon Fraser Univ., Vancouver, BC, Canada ; Saif, M.

This paper proposes a second-order sliding mode observer for fault diagnosis (FD) of a class of uncertain dynamical systems. In the proposed FD scheme, a modified super-twisting second-order sliding mode algorithm is firstly established to observe the system state in the presence of uncertainties and disturbances, and then the observer input is designed by using a PID-type iterative learning algorithm to detect, isolate, and estimate faults. The convergence of the sliding mode algorithm and the parameter update law for the iterative learning estimator are both theoretically and rigorously studied. Finally, the proposed fault diagnosis scheme is applied to the dynamics of a satellite with flexible appendages, and the simulation results demonstrate its effectiveness.

Published in:

Systems Journal, IEEE  (Volume:4 ,  Issue: 1 )