Journal
AUTOMATICA
Volume 45, Issue 3, Pages 836-841Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2008.10.028
Keywords
Stochastic systems; Nonlinear systems; Uncertain systems; Time-delay; Missing measurements
Funding
- Shanghai Natural Science Foundation [07ZR14002]
- Engineering and Physical Sciences Research Council (EPSRC) of the UK [GR/S27658/01]
- Royal Society of the UK
- Nuffield Foundation of the UK [NAL/00630/G]
- Alexander von Humboldt Foundation of Germany
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This paper is concerned with the filtering problem for a class of discrete-time uncertain stochastic nonlinear time-delay systems with both the probabilistic missing measurements and external stochastic disturbances. The measurement missing phenomenon is assumed to occur in a random way, and the missing probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution over the interval [0 1]. Such a probabilistic distribution could be any commonly used discrete distribution over the interval [0 1]. The multiplicative stochastic disturbances are in the form of a scalar Gaussian white noise with unit variance. The purpose of the addressed filtering problem is to design a filter such that, for the admissible random measurement missing, stochastic disturbances, norm-bounded uncertainties as well as stochastic nonlinearities, the error dynamics of the filtering process is exponentially mean-square stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the exponential mean-square stability of the filtering error, and then the filter parameters are characterized by the solution to a set of LMIs. Illustrative examples are exploited to show the effectiveness of the proposed design procedures. (C) 2008 Elsevier Ltd. All rights reserved.
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