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

机译:具有传感器饱和,量化和随机丢包的非线性随机系统的H_∞滤波

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摘要

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.
机译:本文涉及一类非线性随机系统的H_∞滤波问题,该系统在不可靠的通信信道上会发生传感器饱和。一类具有全局Lipschitz非线性和随机噪声(取决于状态和外部干扰)的随机系统描述了所研究的工厂。传感器饱和度的特性是通过分解方法来处理的,该分解方法比在现有工作中将传感器饱和度和网络引起的现象分别考虑的方法更普遍。设备与过滤器之间的通信链路是不可靠的网络通道,并且将输出对数量化和数据包丢失的影响一并考虑在内。这项工作的目的是通过采用不完整的输出测量来设计全阶滤波器,从而确保估计误差的动态随机性。研究了过滤器分析和综合问题,并提供了所需过滤器的明确表达。最后,通过数值模拟说明了设计滤波技术的有效性。

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