Please use this identifier to cite or link to this item:
Title: H-infinity filtering with randomly occurring sensor saturations and missing measurements
Authors: Wang, Z
Shen, B
Liu, X
Keywords: Randomly occurring sensor saturations;Missing measurements;Nonlinear systems;Regional H∞ filters;Random incomplete information
Issue Date: 2012
Publisher: Elsevier
Citation: Automatica, 48(3): 556 - 562, Mar 2012
Abstract: In this paper, the H∞ filtering problem is investigated for a class of nonlinear systems with randomly occurring incomplete information. The considered incomplete information includes both the sensor saturations and the missing measurements. A new phenomenon of sensor saturation, namely, randomly occurring sensor saturation (ROSS), is put forward in order to better reflect the reality in a networked environment such as sensor networks. A novel sensor model is then established to account for both the ROSS and missing measurement in a unified representation by using two sets of Bernoulli distributed white sequences with known conditional probabilities. Based on this sensor model, a regional H∞ filter with a certain ellipsoid constraint is designed such that the filtering error dynamics is locally mean-square asymptotically stable and the H∞-norm requirement is satisfied. Note that the regional l2 gain filtering feature is specifically developed for the random saturation nonlinearity. The characterization of the desired filter gains is derived in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite program method. Finally, a simulation example is employed to show the effectiveness of the filtering scheme proposed in this paper.
Description: This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 Elsevier
ISSN: 0005-1098
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.pdf201.92 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.