H∞H∞ filtering for nonlinear stochastic systems with sensor saturation, quantization and random packet losses

This paper is concerned with the H∞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.

► We are concerned with the robust filtering problem for networked stochastic systems. ► Output saturation, quantization and random packet loss are taken into consideration. ► The effect of sensor saturation is handled by a decomposition approach. ► The proposed approach is more general than those in the existing work.