Title :
An approach to optimally robust fault detection and diagnosis
Author :
Nazih, Mechbal ; Michel, Vergé
Author_Institution :
Lab. de Mecanique des Systemes et des Procedes, ENSAM, Paris, France
Abstract :
In this paper, an original approach for robust fault detection and diagnosis (RFDD) is presented. We propose a method that makes use of H 2 and H∞ polynomial estimators to elaborate a RFDD procedure. The system considered is linear, stochastic and subject to noise, unknown inputs and uncertainties. The residual is obtained via factorization approach and then parameterized by H2 and H∞ polynomial estimators to generate optimal robust fault detectors (ORFD). Adaptive thresholds are also derived with respect to an evaluation index. The results are illustrated by simulations on an actual rolling system
Keywords :
H∞ optimisation; fault diagnosis; identification; linear systems; noise; stochastic systems; uncertain systems; H∞ polynomial estimators; H2 polynomial estimators; ORFD; RFDD; adaptive thresholds; evaluation index; factorization; linear stochastic system; noise; optimal robust fault detectors; optimally robust fault diagnosis; rolling system; uncertainties; unknown inputs; Fault detection; Fault diagnosis; Hydrogen; Mathematical model; Noise robustness; Polynomials; Signal processing; Stochastic resonance; Stochastic systems; Uncertainty;
Conference_Titel :
Control Applications, 2001. (CCA '01). Proceedings of the 2001 IEEE International Conference on
Conference_Location :
Mexico City
Print_ISBN :
0-7803-6733-2
DOI :
10.1109/CCA.2001.973844
