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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Bibliographic Details
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
Description
Summary: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.