Journal
IEEE SIGNAL PROCESSING LETTERS
Volume 16, Issue 5, Pages 442-445Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2009.2016730
Keywords
Linear matrix inequality (LMI); parameter uncertainties; robust H-infinity filtering; sensor gain reduction
Categories
Funding
- NSFC [60721003, 60736026]
- Basic Research 973 [2009CB320602]
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In this paper, a new robust H-infinity filtering problem is investigated for a class of time-varying nonlinear system with norm-bounded parameter uncertainties, bounded state delay, sector-bounded nonlinearity and probabilistic sensor gain faults. The probabilistic sensor reductions are modeled by using a random variable that obeys a specific distribution in a known interval [alpha, beta], which accounts for the following two phenomenon: 1) signal stochastic attenuation in unreliable analog channel and 2) random sensor gain reduction in severe environment. The main task is to design a robust H-infinity filter such that, for all possible uncertain measurements, system parameter uncertainties, nonlinearity as well as time-varying delays, the filtering error dynamics is asymptotically mean-square stable with a prescribed H-infinity performance level. A sufficient condition for the existence or such a filter is presented in terms of the feasibility of a certain linear matrix inequality (LMI). A numerical example is introduced to illustrate the effectiveness and applicability of the proposed methodology.
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