Abstract and Applied Analysis

Deconvolution Filtering for Nonlinear Stochastic Systems with Randomly Occurring Sensor Delays via Probability-Dependent Method

Yuqiang Luo, Guoliang Wei, Hamid Reza Karimi, and Licheng Wang

Full-text: Open access

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.

Article information

Source
Abstr. Appl. Anal., Volume 2013, Special Issue (2013), Article ID 814187, 12 pages.

Dates
First available in Project Euclid: 26 February 2014

Permanent link to this document
https://projecteuclid.org/euclid.aaa/1393447716

Digital Object Identifier
doi:10.1155/2013/814187

Mathematical Reviews number (MathSciNet)
MR3068873

Zentralblatt MATH identifier
07095385

Citation

Luo, Yuqiang; Wei, Guoliang; Karimi, Hamid Reza; Wang, Licheng. Deconvolution Filtering for Nonlinear Stochastic Systems with Randomly Occurring Sensor Delays via Probability-Dependent Method. Abstr. Appl. Anal. 2013, Special Issue (2013), Article ID 814187, 12 pages. doi:10.1155/2013/814187. https://projecteuclid.org/euclid.aaa/1393447716


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