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Structured fault detection filters for LPV systems modeled in an LFR manner
Author(s) -
Henry D.
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.1258
Subject(s) - fault detection and isolation , control theory (sociology) , filter (signal processing) , linear system , projection (relational algebra) , representation (politics) , linear matrix inequality , lemma (botany) , residual , fault (geology) , computer science , filter design , mathematics , matrix (chemical analysis) , algorithm , mathematical optimization , actuator , mathematical analysis , artificial intelligence , control (management) , seismology , geology , materials science , law , ecology , composite material , biology , political science , computer vision , poaceae , politics
SUMMARY This paper investigates the design of robust‡ fault detection and isolation filters for linear parameter‐varying systems modeled in a linear fractional representation fashion. The goal is to obtain structured fault detection filters with enhanced fault transmission H − gain and large H ∞ nuisance attenuation. It is shown by means of the scaling matrices technique and the projection lemma that the synthesis of the residual structuring and the filter state‐space matrices can be performed simultaneously using linear matrix inequality optimization techniques. Computational aspects are discussed and it is shown that the proposed solution is structurally well defined. Closed‐loop time simulations demonstrate the efficiency of the proposed method. Copyright © 2011 John Wiley & Sons, Ltd.