H∞ filtering for uncertain time‐varying systems with multiple randomly occurred nonlinearities and successive packet dropouts |
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Authors: | Bo Shen Zidong Wang Huisheng Shu Guoliang Wei |
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Affiliation: | 1. School of Information Science and Technology, Donghua University, Shanghai 200051, People's Republic of China;2. Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex UB8 3PH, U.K. |
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Abstract: | This paper is concerned with the robust H∞ finite‐horizon filtering problem for discrete time‐varying stochastic systems with multiple randomly occurred sector‐nonlinearities (MROSNs) and successive packet dropouts. MROSNs are proposed to model a class of sector‐like nonlinearities that occur according to the multiple Bernoulli distributed white sequences with a known conditional probability. Different from traditional approaches, in this paper, a time‐varying filter is designed directly for the addressed system without resorting to the augmentation of system states and measurement, which helps reduce the filter order. A new H∞ filtering technique is developed by means of a set of recursive linear matrix inequalities that depend on not only the current available state estimate but also the previous measurement, therefore ensuring a better accuracy. Finally, two illustrative examples are used to demonstrate the effectiveness and applicability of the proposed filter design scheme. Copyright © 2010 John Wiley & Sons, Ltd. |
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Keywords: | stochastic systems discrete time‐varying systems H∞ filtering recursive linear matrix inequalities multiple randomly occurred nonlinearities successive packet dropouts |
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