Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/110592
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Type: Journal article
Title: Robust filtering for nonlinear nonhomogeneous Markov jump systems by fuzzy approximation approach
Author: Yin, Y.
Shi, P.
Liu, F.
Teo, K.
Lim, C.-.C.
Citation: IEEE Transactions on Cybernetics, 2015; 45(9):1706-1716
Publisher: IEEE
Issue Date: 2015
ISSN: 2168-2267
2168-2275
Statement of
Responsibility: 
Yanyan Yin, Peng Shi, Fei Liu, Kok Lay Teo and Cheng-Chew Lim
Abstract: This paper addresses the problem of robust fuzzy L₂ - L∞ filtering for a class of uncertain nonlinear discrete-time Markov jump systems (MJSs) with nonhomogeneous jump processes. The Takagi-Sugeno fuzzy model is employed to represent such nonlinear nonhomogeneous MJS with norm-bounded parameter uncertainties. In order to decrease conservation, a polytope Lyapunov function which evolves as a convex function is employed, and then, under the designed mode-dependent and variation-dependent fuzzy filter which includes the membership functions, a sufficient condition is presented to ensure that the filtering error dynamic system is stochastically stable and that it has a prescribed L₂ - L∞ performance index. Two simulated examples are given to demonstrate the effectiveness and advantages of the proposed techniques.
Keywords: Fuzzy L2 − L∞ filtering; Markov jump system (MJS); nonhomogeneous processes; uncertain nonlinear system
Rights: © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
RMID: 0030022735
DOI: 10.1109/TCYB.2014.2358680
Grant ID: http://purl.org/au-research/grants/arc/DP140102180
http://purl.org/au-research/grants/arc/LP140100471
Appears in Collections:Electrical and Electronic Engineering publications

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