Observer-based robust process fault detection and diagnosis for a satellite system with flexible appendages
Proceedings of the IEEE Conference on Decision and Control
This paper presents a novel observer-based robust process fault detection and diagnosis (FDD) scheme in a class of nonlinear dynamic systems. The proposed observer synthesizes sliding mode techniques and PID-type iterative learning estimators. The observer inputs, which are designed to isolate unci estimate faults, are iteratively computed using the proportional, integral, and derivative information about the output eastimation error. An adaptive algorithm is adopted to update the parameters of the observer. Moreover, robustness, sensitivity, and stability of this fault detection and diagnosis scheme are theoretically analyzed. Finally, the proposed algorithm is applied to a satellite system with flexible appendages, and simulation results illustrate its effectiveness. © 2006 IEEE.
Wu, Qing and Saif, Mehrdad. (2006). Observer-based robust process fault detection and diagnosis for a satellite system with flexible appendages. Proceedings of the IEEE Conference on Decision and Control, 2183-2188.