Fuzzy Hyperbolic Neural Network Model and Its Application in H ∞Filter Design
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Delay-dependent H∞ filter design for discrete-time fuzzy systems with time-varying delays
IEEE Transactions on Fuzzy Systems
On the estimation of parameters of Takagi-Sugeno fuzzy filte
IEEE Transactions on Fuzzy Systems
Delay-dependent H∞filtering for nonlinear systems via T-S fuzzy model approach
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Unbiased H∞filtering for a class of stochastic systems with time-varying delay
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
IEEE Transactions on Fuzzy Systems
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Decentralized H∞ filter design for discrete-time interconnected fuzzy systems
IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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IEEE Transactions on Fuzzy Systems
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This paper studies H∞ fuzzy filtering design for state estimation of nonlinear discrete-time systems with bounded but unknown disturbances. First, the Takagi and Sugeno (1985) fuzzy model is proposed to represent a nonlinear system. Next, using a linear matrix inequality (LMI) approach, the H∞ fuzzy filtering problems are characterized in terms of a linear matrix inequality problem (LMIP). The LMIP can be efficiently solved using convex optimization techniques. Simulation examples are given to illustrate the design procedure and the applicability of the proposed method. The results indicate that the proposed method is suitable for practical applications