Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/11811
Title: Distributed H ∞ state estimation for stochastic delayed 2-D systems with randomly varying nonlinearities over saturated sensor networks
Authors: Liang, J
Wang, Z
Hayat, T
Alsaedi, A
Keywords: Two-dimensional(2-D)systems;Distributed state estimation;H∞ index;Randomly varying nonlinearities (RVNs);Sensor saturation
Issue Date: 2015
Publisher: Elsevier
Citation: Information Sciences, pp.1–17, (2015)
Abstract: In this paper, the distributed H ∞ state estimation problem is investigated for the two-dimensional (2-D) time-delay systems. The target plant is characterized by the generalized Fornasini-Marchesini 2-D equations where both stochastic disturbances and randomly varying nonlinearities (RVNs) are considered. The sensor measurement outputs are subject to saturation restrictions due to the physical limitations of the sensors. Based on the available measurement outputs from each individual sensor and its neighboring sensors, the main purpose of this paper is to design distributed state estimators such that not only the states of the target plant are estimated but also the prescribed H ∞ disturbance attenuation performance is guaranteed. By defining an energy-like function and utilizing the stochastic analysis as well as the inequality techniques, sufficient conditions are established under which the augmented estimation error system is globally asymptotically stable in the mean square and the prescribed H ∞ performance index is satisfied. Furthermore, the explicit expressions of the individual estimators are also derived. Finally, numerical example is exploited to demonstrate the effectiveness of the results obtained in this paper.
URI: http://www.sciencedirect.com/science/article/pii/S0020025515008300
http://bura.brunel.ac.uk/handle/2438/11811
DOI: http://dx.doi.org/10.1016/j.ins.2015.11.020
ISSN: 0020-0255
Appears in Collections:Dept of Computer Science Research Papers

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