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Robust fuzzy filter design for nonlinear systems with persistent bounded disturbances

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1 Author(s)
Chung-Shi Tseng ; Dept. of Electr. Eng., Ming Hsin Univ. of Sci. & Technol., Hsin Chu

To date, nonlinear Linfin-gain filtering problems have not been solved by conventional methods for nonlinear dynamic systems with persistent bounded disturbances. This study introduces a fuzzy filtering design to deal with the nonlinear Linfin-gain filtering problem. First, the Takagi and Sugeno fuzzy model is employed to approximate the nonlinear dynamic system. Next, based on the fuzzy model, a fuzzy filter is developed to minimize the upper bound of Linfin-gain of the estimation error under some linear matrix inequality (LMI) constraints. Therefore, the nonlinear Linfin-gain filtering problem is transformed into a suboptimal filtering problem, i.e., to minimize the upper bound of the Linfin-gain of the estimation error subject to some LMI constraints. In this situation, the nonlinear Linfin-gain filtering problem can be easily solved by an LMI-based optimization method. The proposed methods, which efficiently attenuate the peak of estimation error due to persistent bounded disturbances, extend the L infin-gain filtering problems from linear dynamic systems to nonlinear dynamic systems

Published in:

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:36 ,  Issue: 4 )

Date of Publication:

Aug. 2006

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