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Variance‐constrained robust estimation for uncertain systems with multiple packet dropouts
Author(s) -
Wang Baofeng,
Guo Ge,
Yue Wei
Publication year - 2011
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.1027
Subject(s) - network packet , bounded function , control theory (sociology) , mathematics , filter (signal processing) , filtering problem , variance (accounting) , upper and lower bounds , invariant (physics) , representation (politics) , mathematical optimization , computer science , filter design , control (management) , mathematical analysis , business , mathematical physics , computer vision , politics , political science , law , computer network , accounting , artificial intelligence
SUMMARY This paper deals with variance‐constrained filtering problem in networked control systems (NCSs) with multiple packet dropouts. The system is subject to time‐invariant norm‐bounded parameter uncertainties in both the state and measurement matrices. Based on a model of multiple packet dropouts, the consecutive packet losses rate is transformed into a stochastic parameter in the system representation. The problem addressed is to design a linear filter such that, for all admissible parameter uncertainties and consecutive packet dropouts, the error state of the filtering process is mean square bounded, and the steady‐state variance of the estimation error for each state is not more than the individual prescribed upper bound. The conditions for the existence of a desired filter are obtained in terms of the solutions of two algebraic matrix inequalities, based on which an explicit expression of the robust filter is derived. Finally, an algorithm for solving the coupling inequalities, which is not optimal but practical, is provided and applied to some numerical examples. Copyright © 2011 John Wiley & Sons, Ltd.