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- W2465921773 abstract "This paper is concerned with the state estimation problem for a class of nonlinear cyber-physical systems (CPSs) where the nonlinear dynamical physical process is approximated by a Takagi-Sugeno fuzzy model. The physical plant is measured by a set of wireless sensors and the sensors communicate with the remote estimator via a communication channel. In the considered CPS, the randomly occurring sensor saturation, signal quantization, packet dropouts as well as the medium access constraint are studied in a unified framework. We develop a sufficient condition such that the filtering error system is asymptotically stable in the mean-square sense and also with a prescribed H <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>∞</sub> performance level. The filter gain parameters are determined by solving a convex optimization problem. Finally, the simulation study on the networked truck-trailer system is presented to show the effectiveness of the proposed estimator design." @default.
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- W2465921773 date "2017-08-01" @default.
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- W2465921773 title "Robust Fuzzy-Model-Based Filtering for Nonlinear Cyber-Physical Systems With Multiple Stochastic Incomplete Measurements" @default.
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- W2465921773 doi "https://doi.org/10.1109/tsmc.2016.2551200" @default.
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