Journal of Applied Mathematics
Volume 2012 (2012), Article ID 402480, 25 pages
Research Article

Robust Filtering for Uncertain Discrete-Time Fuzzy Stochastic Systems with Sensor Nonlinearities and Time-Varying Delay

1College of Computer and Information, Hohai University, Changzhou 213022, China
2Changzhou Key Laboratory of Sensor Networks and Environmental Sensing, Changzhou 213022, China
3Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology, Changzhou 213022, China
4School of Mathematical Sciences, Anhui University, Hefei 230601, China
5Department of Mathematics and Physics, Hohai University, Changzhou 213022, China

Received 10 October 2012; Revised 7 December 2012; Accepted 11 December 2012

Academic Editor: Hak-Keung Lam

Copyright © 2012 Mingang Hua et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The robust filtering problem for a class of uncertain discrete-time fuzzy stochastic systems with sensor nonlinearities and time-varying delay is investigated. The parameter uncertainties are assumed to be time varying norm bounded in both the state and measurement equations. By using the Lyapunov stability theory and some new relaxed techniques, sufficient conditions are proposed to guarantee the robustly stochastic stability with a prescribed performance level of the filtering error system for all admissible uncertainties, sensor nonlinearities, and time-varying delays. These conditions are dependent on the lower and upper bounds of the time-varying delays and are obtained in terms of a linear matrix inequality (LMI). Finally, two simulation examples are provided to illustrate the effectiveness of the proposed methods.