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

Yin, Y. and Shi, P. and Liu, F. and Teo, K.L. and Lim, C. 2015. Robust Filtering for Nonlinear Nonhomogeneous Markov Jump Systems by Fuzzy Approximation Approach. IEEE Transactions on Cybernetics. 45 (9): pp. 1706-1716.

Source Title

IEEE Transactions on Cybernetics

DOI

10.1109/TCYB.2014.2358680

ISSN

2168-2267

Remarks

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URI

http://hdl.handle.net/20.500.11937/42887

Collection

Curtin Research Publications

Abstract

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.