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2013 Deconvolution Filtering for Nonlinear Stochastic Systems with Randomly Occurring Sensor Delays via Probability-Dependent Method
Yuqiang Luo, Guoliang Wei, Hamid Reza Karimi, Licheng Wang
Abstr. Appl. Anal. 2013(SI40): 1-12 (2013). DOI: 10.1155/2013/814187

Abstract

This paper deals with a robust H deconvolution filtering problem for discrete-time nonlinear stochastic systems with randomly occurring sensor delays. The delayed measurements are assumed to occur in a random way characterized by a random variable sequence following the Bernoulli distribution with time-varying probability. The purpose is to design an H deconvolution filter such that, for all the admissible randomly occurring sensor delays, nonlinear disturbances, and external noises, the input signal distorted by the transmission channel could be recovered to a specified extent. By utilizing the constructed Lyapunov functional relying on the time-varying probability parameters, the desired sufficient criteria are derived. The proposed H deconvolution filter parameters include not only the fixed gains obtained by solving a convex optimization problem but also the online measurable time-varying probability. When the time-varying sensor delays occur randomly with a time-varying probability sequence, the proposed gain-scheduled filtering algorithm is very effective. The obtained design algorithm is finally verified in the light of simulation examples.

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Yuqiang Luo. Guoliang Wei. Hamid Reza Karimi. Licheng Wang. "Deconvolution Filtering for Nonlinear Stochastic Systems with Randomly Occurring Sensor Delays via Probability-Dependent Method." Abstr. Appl. Anal. 2013 (SI40) 1 - 12, 2013. https://doi.org/10.1155/2013/814187

Information

Published: 2013
First available in Project Euclid: 26 February 2014

zbMATH: 07095385
MathSciNet: MR3068873
Digital Object Identifier: 10.1155/2013/814187

Rights: Copyright © 2013 Hindawi

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Vol.2013 • No. SI40 • 2013
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