Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/6691
Title: Distributed H∞ state estimation with stochastic parameters and nonlinearities through sensor networks: The finite-horizon case
Authors: Ding, D
Wang, Z
Dong, H
Shu, H
Keywords: Discrete time-varying systems;Distributed H∞ state estimation;Recursive Riccati difference equations;Sensor networks;Stochastic nonlinearities;Stochastic parameters
Issue Date: 2012
Publisher: Elsevier
Citation: Automatica, 48(8): 1575 - 1585, Aug 2012
Abstract: This paper deals with the distributed H∞ state estimation problem for a class of discrete time-varying nonlinear systems with both stochastic parameters and stochastic nonlinearities. The system measurements are collected through sensor networks with sensors distributed according to a given topology. The purpose of the addressed problem is to design a set of time-varying estimators such that the average estimation performance of the networked sensors is guaranteed over a given finite-horizon. Through available output measurements from not only the individual sensor but also its neighboring sensors, a necessary and sufficient condition is established to achieve the H∞ performance constraint, and then the estimator design scheme is proposed via a certain H2-type criterion. The desired estimator parameters can be obtained by solving coupled backward recursive Riccati difference equations (RDEs). A numerical simulation example is provided to demonstrate the effectiveness and applicability of the proposed estimator design approach.
Description: This is the post-print version of the final paper published in Automatica. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.
URI: http://www.sciencedirect.com/science/article/pii/S0005109812002439
http://bura.brunel.ac.uk/handle/2438/6691
DOI: http://dx.doi.org/10.1016/j.automatica.2012.05.070
ISSN: 0005-1098
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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