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Fault detection and isolation in linear parameter‐varying descriptor systems via proportional integral observer
Author(s) -
Hamdi H.,
Rodrigues Mickael,
Mechmeche C.,
Theilliol D.,
Braiek N. Benhadj
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.1260
Subject(s) - control theory (sociology) , observer (physics) , fault detection and isolation , hypercube , mathematics , linear matrix inequality , linear system , stability (learning theory) , actuator , representation (politics) , domain (mathematical analysis) , computer science , mathematical optimization , artificial intelligence , control (management) , mathematical analysis , physics , discrete mathematics , quantum mechanics , machine learning , politics , political science , law
SUMMARY The main contribution of this paper is the design of a polytopic unknown inputs proportional integral observer (UIPIO) for linear parameter‐varying (LPV) descriptor systems. This observer is used for actuator fault detection and isolation. The proposed method is based on the representation of the LPV descriptor systems in a polytopic form. Its parameters evolve in an hypercube domain. The designed polytopic UIPIO is also able to estimate both the states and the unknown inputs of the LPV descriptor system. Stability conditions of such observer are expressed in terms of linear matrix inequalities. An example illustrates the performances of such polytopic UIPIO. Copyright © 2011 John Wiley & Sons, Ltd.