Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach

This paper addresses the problem of robust fuzzy L2 - L∞ filtering for a class of uncertain nonlinear discretetime 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 uncer...

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Main Authors: Yin, Y., Shi, Peng, Liu, F., Teo, Kok Lay, Lim, C.
Format: Journal Article
Published: Institute of Electrical and Electronics Engineers 2015
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/42887
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author Yin, Y.
Shi, Peng
Liu, F.
Teo, Kok Lay
Lim, C.
author_facet Yin, Y.
Shi, Peng
Liu, F.
Teo, Kok Lay
Lim, C.
author_sort Yin, Y.
building Curtin Institutional Repository
collection Online Access
description This paper addresses the problem of robust fuzzy L2 - L∞ filtering for a class of uncertain nonlinear discretetime 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.
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institution Curtin University Malaysia
institution_category Local University
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publishDate 2015
publisher Institute of Electrical and Electronics Engineers
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spelling curtin-20.500.11937-428872018-10-18T00:59:05Z Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach Yin, Y. Shi, Peng Liu, F. Teo, Kok Lay Lim, C. uncertain nonlinear system nonhomogeneous processes Markov jump system (MJS) Fuzzy L2 - L∞ filtering This paper addresses the problem of robust fuzzy L2 - L∞ filtering for a class of uncertain nonlinear discretetime 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. 2015 Journal Article http://hdl.handle.net/20.500.11937/42887 10.1109/TCYB.2014.2358680 Institute of Electrical and Electronics Engineers fulltext
spellingShingle uncertain nonlinear system
nonhomogeneous processes
Markov jump system (MJS)
Fuzzy L2 - L∞ filtering
Yin, Y.
Shi, Peng
Liu, F.
Teo, Kok Lay
Lim, C.
Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach
title Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach
title_full Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach
title_fullStr Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach
title_full_unstemmed Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach
title_short Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach
title_sort robust filtering for nonlinear nonhomogeneous markov jump systems by fuzzy approximation approach
topic uncertain nonlinear system
nonhomogeneous processes
Markov jump system (MJS)
Fuzzy L2 - L∞ filtering
url http://hdl.handle.net/20.500.11937/42887