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Fault diagnosis for a class of descriptor linear parameter‐varying systems
Author(s) -
AstorgaZaragoza C. M.,
Theilliol D.,
Ponsart J. C.,
Rodrigues M.
Publication year - 2012
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.1259
Subject(s) - observer (physics) , control theory (sociology) , fault (geology) , lyapunov function , mathematics , linear matrix inequality , class (philosophy) , stability (learning theory) , computer science , estimation theory , matrix (chemical analysis) , fault detection and isolation , linear system , mathematical optimization , algorithm , nonlinear system , artificial intelligence , control (management) , machine learning , mathematical analysis , physics , materials science , quantum mechanics , seismology , actuator , composite material , geology
SUMMARY In this paper, a model‐based fault estimation method for a particular class of discrete‐time descriptor linear parameter‐varying systems is developed. The main contribution of this work consists in the design of an observer that performs simultaneously both, the states estimation and the fault magnitude vectors, considered as unknown inputs. The conditions for the existence of such observer are given. Such conditions guarantee the observer stability and they are proved through a Lyapunov analysis combined with a linear matrix inequalities formulation. The fault estimation scheme is evaluated through numerical simulations. Copyright © 2011 John Wiley & Sons, Ltd.