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Networked continuous-time filtering for quadratically inner-bounded time-delay systems with multirate sampling

机译:具有多速率采样的二次内界时滞系统的网络连续时间滤波

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摘要

This paper addresses the networked H infinity filtering problem for time-delay systems with quadratically inner-bounded nonlinearities, where the different output sub-vectors of the systems are sampled respec-tively by sensor groups with different sampling periods (i. e., multirate sampling or MRS). The multirate sampled data are transmitted to a filter through multiple communication channels with network-induced packet dropouts and time-varying transmission delays. Considering MRS's asynchronous behavior, we propose a matching mechanism to synchronize the successfully transmitted sampled data of the non-linear system and the sampled data of a filter. Based on the matched sampled data, two types of new continuous-time filters are presented to estimate the objective signal of the nonlinear system. In view of the fact that the lifting technique may fail to model the nonlinear system, the resultant filtering error systems are modeled as continuous-time nonlinear systems with several sawtooth delays. By the Lyapunov-Krasovskii functional approach, some sufficient conditions are obtained to ensure that the filtering error systems are stable with a prescribed H infinity performance level, and the design methods of the two filters are given. Finally, a numerical example shows the effectiveness of our proposed methods. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:本文解决了具有二次内界非线性的时滞系统的网络H无限滤波问题,其中系统的不同输出子矢量分别由具有不同采样周期的传感器组采样(即多速率采样或MRS) )。多速率采样数据通过具有网络引起的数据包丢失和时变传输延迟的多个通信通道传输到滤波器。考虑到MRS的异步行为,我们提出了一种匹配机制来使非线性系统成功传输的采样数据与滤波器的采样数据同步。基于匹配的采样数据,提出了两种新型的连续时间滤波器来估计非线性系统的目标信号。考虑到举升技术可能无法对非线性系统进行建模,因此将所得的滤波误差系统建模为具有几个锯齿延迟的连续时间非线性系统。通过Lyapunov-Krasovskii函数方法,获得了一些足以确保滤波误差系统在规定的H无穷大性能水平下稳定的条件,并给出了两个滤波器的设计方法。最后,一个数值例子说明了我们提出的方法的有效性。 (C)2017富兰克林研究所。由Elsevier Ltd.出版。保留所有权利。

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  • 来源
    《Journal of the Franklin Institute》 |2017年第17期|7946-7967|共22页
  • 作者单位

    Shanxi Univ, Sch Math Sci, Taiyuan 030006, Shanxi, Peoples R China;

    Shanxi Univ, Sch Math Sci, Taiyuan 030006, Shanxi, Peoples R China;

    Shanxi Univ, Sch Math Sci, Taiyuan 030006, Shanxi, Peoples R China;

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  • 正文语种 eng
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  • 入库时间 2022-08-18 02:57:40

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