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Title: Distributed state estimation in sensor networks with randomly occurring nonlinearities subject to time delays
Authors: Liang, J
Wang, Z
Shen, B
Liu, X
Issue Date: 2012
Publisher: Association for Computing Machinery (ACM)
Citation: ACM Transactions on Sensor Networks, 9(1): 4, Nov 2012
Abstract: This article is concerned with a new distributed state estimation problem for a class of dynamical systems in sensor networks. The target plant is described by a set of differential equations disturbed by a Brownian motion and randomly occurring nonlinearities (RONs) subject to time delays. The RONs are investigated here to reflect network-induced randomly occurring regulation of the delayed states on the current ones. Through available measurement output transmitted from the sensors, a distributed state estimator is designed to estimate the states of the target system, where each sensor can communicate with the neighboring sensors according to the given topology by means of a directed graph. The state estimation is carried out in a distributed way and is therefore applicable to online application. By resorting to the Lyapunov functional combined with stochastic analysis techniques, several delay-dependent criteria are established that not only ensure the estimation error to be globally asymptotically stable in the mean square, but also guarantee the existence of the desired estimator gains that can then be explicitly expressed when certain matrix inequalities are solved. A numerical example is given to verify the designed distributed state estimators.
Description: This is the post-print version of the Article. The official published version can be accessed from the links below - Copyright @ 2012 ACM.
ISSN: 1550-4859
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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