The H_∞ filtering problem for a class of networked nonlinear Markovian jump systems subject to randomly occurring distributed delays, nonlinearities, quantization effects, missing measurements and sensor saturation is investigated in this paper. The measurement missing phenomenon is characterized via a random variable obeying the Bernoulli stochastic distribution. Moreover, due to bandwidth limitations, the measurement output is quantized using a logarithmic quantizer and then transmitted to the filter. Further, the output measurements are affected by sensor saturation since the communication links between the system and the filter are unreliable and is described by sector nonlinearities. The objective of this work is to design a quantized resilient filter that guarantees not only the stochastic stability of the augmented filtering error system but also a prespecified level of H_∞ performance. Sufficient conditions for the existence of desired filter are established with the aid of proper Lyapunov–Krasovskii functional and linear matrix inequality approach together with stochastic analysis theory. Finally, a numerical example is presented to validate the developed theoretical results.

该^ h _∞研究了一类具有随机分布的时滞，非线性，量化效应，测量值丢失和传感器饱和的网络非线性马尔可夫跳跃系统的滤波问题。测量遗漏现象的特征在于服从伯努利随机分布的随机变量。此外，由于带宽限制，测量输出使用对数量化器进行量化，然后传输到滤波器。此外，输出测量值受传感器饱和度的影响，因为系统和滤波器之间的通信链接不可靠，并且通过扇区非线性来描述。^ h _∞的性能。借助适当的Lyapunov–Krasovskii泛函和线性矩阵不等式方法以及随机分析理论，可以确定存在所需滤波器的充分条件。最后，通过数值例子验证了所开发的理论结果。