Stabilization of linear systems in the presence of output measurement saturation
Systems & Control Letters
Robust filtering for uncertain delay systems under sampled measurements
Signal Processing
Robust filtering for jumping systems with mode-dependent delays
Signal Processing
Brief paper: Control under quantization, saturation and delay: An LMI approach
Automatica (Journal of IFAC)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Filtering for discrete fuzzy stochastic systems with sensor nonlinearities
IEEE Transactions on Fuzzy Systems
New passivity analysis for neural networks with discrete and distributed delays
IEEE Transactions on Neural Networks
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This paper is concerned with the H"~ filtering problem for a class of nonlinear stochastic systems subject to sensor saturation over unreliable communication channel. The investigated plant is described by a class of stochastic systems with global Lipschitz nonlinearities and random noise depending on state and external-disturbance. The characteristic of sensor saturation is handled by a decomposition approach which is more general than those in the existing work where the sensor saturation and network-induced phenomenon were considered separately. The communication links between the plant and filter are unreliable network channels, and the effects of output logarithmic quantization and data packet losses are considered together. The purpose of this work is to design a full-order filter by employing the incomplete output measurements such that the dynamics of the estimation error is guaranteed to be stochastically stable. Both filter analysis and synthesis problems are investigated, and the explicit expression of the desired filters is also provided. Finally, a numerical simulation is illustrated to show the effectiveness of the designing filtering technique.