Robust filtering for nonlinear nonhomogeneous Markov jump systems by fuzzy approximation approach
Date
2015
Authors
Yin, Y.
Shi, P.
Liu, F.
Teo, K.
Lim, C.-C.
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Journal article
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IEEE Transactions on Cybernetics, 2015; 45(9):1706-1716
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Yanyan Yin, Peng Shi, Fei Liu, Kok Lay Teo and Cheng-Chew Lim
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Abstract
This paper addresses the problem of robust fuzzy Lā - Lā 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 Lā - Lā performance index. Two simulated examples are given to demonstrate the effectiveness and advantages of the proposed techniques.
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