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State estimation for time‐delay systems with probabilistic sensor gain reductions
Author(s) -
He Xiao,
Wang Zidong,
Zhou D. H.
Publication year - 2008
Publication title -
asia‐pacific journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.348
H-Index - 35
eISSN - 1932-2143
pISSN - 1932-2135
DOI - 10.1002/apj.190
Subject(s) - control theory (sociology) , probabilistic logic , reduction (mathematics) , estimator , linear matrix inequality , attenuation , computer science , variable (mathematics) , state (computer science) , discrete time and continuous time , mathematics , mathematical optimization , algorithm , control (management) , statistics , mathematical analysis , physics , geometry , artificial intelligence , optics
This paper presents a new state estimation problem for a class of time‐delay systems with probabilistic sensor gain faults. The sensor gain reductions are described by a stochastic variable that obeys the uniform distribution in a known interval [α, β], which is a natural reflection of the probabilistic performance deterioration of sensors when gain reduction faults occur. Attention is focused on the design of a state estimator such that for all possible sensor faults and all external disturbances, the filtering error dynamic is asymptotically mean‐square stable as well as fulfils a prescribed disturbance attenuation level. The existence of desired filters is proved to depend on the feasibility of a certain linear matrix inequality (LMI), and a numerical example is given to illustrate the effectiveness of the proposed design approach. Copyright © 2008 Curtin University of Technology and John Wiley & Sons, Ltd.