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Reliable H ∞ filtering for discrete time‐delay Markovian jump systems with partly unknown transition probabilities
Author(s) -
Liu Yisha,
Wang Zidong,
Wang Wei
Publication year - 2011
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.1231
Subject(s) - filter (signal processing) , control theory (sociology) , mathematics , interval (graph theory) , filtering problem , nonlinear system , jumping , jump , filter design , markov process , discrete time and continuous time , computer science , statistics , control (management) , physics , combinatorics , quantum mechanics , artificial intelligence , computer vision , biology , physiology
Abstract In this paper, the reliable H ∞ filtering problem is studied for a class of discrete nonlinear Markovian jump systems with sensor failures and time delays. The transition probabilities of the jumping process are assumed to be partly unknown. The failures of sensors are quantified by a variable taking values in a given interval. The time‐varying delay is unknown with given lower and upper bounds. The purpose of the addressed reliable H ∞ filtering problem is to design a mode‐dependent filter such that the filtering error dynamics is asymptotically mean‐square stable and also achieves a prescribed H ∞ performance level. By using a new Lyapunov–Krasovskii functional and delay‐partitioning technique, sufficient delay‐dependent conditions for the existence of such a filter are obtained. The filter gains are characterized in terms of the solution to a convex optimization problem that can be easily solved by using the semi‐definite programme method. A numerical example is provided to demonstrate the effectiveness of the proposed design approach. Copyright © 2011 John Wiley & Sons, Ltd.