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Quantized H ∞ filtering for Markovian jump LPV systems with intermittent measurements
Author(s) -
Yao Xiuming,
Wu Ligang,
Zheng Wei Xing
Publication year - 2011
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.1809
Subject(s) - control theory (sociology) , jump , markov process , mathematics , statistical physics , computer science , physics , artificial intelligence , control (management) , statistics , quantum mechanics
SUMMARY This paper investigates the problem of quantizedH ∞filtering for a class of discrete‐time linear parameter‐varying systems with Markovian switching under data missing. The measured output of the plant is quantized by a logarithmic mode‐independent quantizer. The data missing phenomenon is modeled by a stochastic variable. The purpose of the problem addressed is to design a full‐orderH ∞filter such that the filtering error dynamics is stochastically stable and the prescribed noise attenuation level in theH ∞sense can be achieved. Sufficient conditions are derived for the existence of such filters in terms of parameterized linear matrix inequalities. Then the corresponding filter synthesis problem is transformed into a convex optimization problem that can be efficiently solved by using standard software packages. A simulation example is utilized to demonstrate the usefulness of the developed theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.