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This paper focuses on the H∞ controller design problem for networked Takagi-Sugeno (T-S) fuzzy systems. The outputs measured by the sensor will be subject to saturation phenomenon and suffer packet dropouts during the transmission through unreliable communication links to the remote controller. Both the sensor saturation and the packet dropouts occur randomly which are governed by the Bernoulli distributed...
An unbiased state filter in linear minimum variance sense is developed for discrete-time stochastic linear systems with unknown inputs and correlated noises, where there is not any prior information for the unknown inputs. When there are multiple sensors, the cross-covariance matrix of filtering errors between any two sensors is derived. Further, the distributed scalar-weighted fusion state filter...
Based on the innovation analysis approach, the estimation error cross-covariance matrices between local estimators based on any two sensors are derived for multi-sensor multi-delay systems with correlated noises. The non-augmented distributed weighted fusion optimal estimators are given based on the optimal weighted fusion estimation algorithm in the linear minimum variance sense. Compared with the...
The filtering fusion problem of a descriptor system with delayed measurements is transferred to the different-step prediction fusion problem of two reduced-order normal subsystems without delayed measurements and with correlated noises. Using projection theory, the cross-covariance matrix of different-step prediction errors between any two sensor subsystems is derived. Based on the fusion algorithm...
This paper is concerned with the estimation problem for discrete-time stochastic linear systems with multiple packet dropouts. Based on a recently developed model for multiple-packet dropouts, the original system is transferred to a stochastic parameter system by augmentation of the state and measurement. The optimal full-order linear filter of the form of employing the received outputs at the current...
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