Robust fusion filtering for multisensor time-varying uncertain systems: the finite horizon case
type: Item
instance of: scholarly article
title: Robust fusion filtering for multisensor time-varying uncertain systems: the finite horizon case
zbMATH Open document ID: 1417.94015
DOI: 10.1155/2016/2720549
author: Xiaoliang Feng
author: Funa Zhou
author: Chenglin Wen
published in: Discrete Dynamics in Nature and Society
publication date: 2019-02-19T00:00:00Z
review text: Summary: The robust \(H \infty\) fusion filtering problem is considered for linear time-varying uncertain systems observed by multiple sensors. A performance index function for this problem is defined as an indefinite quadratic inequality which is solved by the projection method in Krein space. On this basis, a robust centralized finite horizon \(H \infty\) fusion filtering algorithm is proposed. However, this centralized fusion method is with poor real time property, as the number of sensors increases. To resolve this difficulty, within the sequential fusion framework, the performance index function is described as a set of quadratic inequalities including an indefinite quadratic inequality. And a sequential robust finite horizon \(H \infty\) fusion filtering algorithm is given by solving this quadratic inequality group. Finally, two simulation examples for time-varying/time-invariant multisensor systems are exploited to demonstrate the effectiveness of the proposed methods in the respect of the real time property and filtering accuracy.
Mathematics Subject Classification ID: 94A12
Mathematics Subject Classification ID: 93B36
zbMATH DE Number: 7025591
Wikidata QID: Q59123421
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2016/2720549
OpenAlex ID: W2302918896
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description: scientific article; zbMATH DE number 7025591