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Title: Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case
Authors: Shen, B
Wang, Z
Hung, Y
Keywords: Sensor networks;Distributed H∞-consensus filtering;Discrete time-varying systems;Difference linear matrix inequalities;Finite-horizon;Data missing
Issue Date: 2010
Publisher: Elsevier
Citation: Automatica, 46(10): 1682-1688, Oct 2010
Abstract: This paper is concerned with a new distributed H∞-consensus filtering problem over a finite-horizon for sensor networks with multiple missing measurements. The so-called H∞-consensus performance requirement is defined to quantify bounded consensus regarding the filtering errors (agreements) over a finite-horizon. A set of random variables are utilized to model the probabilistic information missing phenomena occurring in the channels from the system to the sensors. A sufficient condition is first established in terms of a set of difference linear matrix inequalities (DLMIs) under which the expected H∞-consensus performance constraint is guaranteed. Given the measurements and estimates of the system state and its neighbors, the filter parameters are then explicitly parameterized by means of the solutions to a certain set of DLMIs that can be computed recursively. Subsequently, two kinds of robust distributed H∞-consensus filters are designed for the system with norm-bounded uncertainties and polytopic uncertainties. Finally, two numerical simulation examples are used to demonstrate the effectiveness of the proposed distributed filters design scheme.
Description: The official published version of the article can be found at the link below.
ISSN: 0005-1098
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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