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Fault detection and control co-design for discrete-time delayed fuzzy networked control systems subject to quantization and multiple packet dropouts

机译:具有量化和多个包丢失的离散时间延迟模糊网络控制系统的故障检测和控制协同设计

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This paper investigates the problem of fault detection (FD) for discrete-time delayed fuzzy networked control systems with quantization and packet dropouts. Different from existing results for FD, the proposed ones are toward closed-loop design problem, that is, the controller gain, and the fault detection filter (FDF) gains are designed simultaneously. The missing phenomenon is assumed to occur, in the communication links for quantizer-to-FDF and controller-to-physical plant, where the missing probability of packet dropouts is governed by an individual random binary distribution, while the quantization errors are treated as sector-bound uncertainties. The discrete-time fuzzy networked system is first transformed into the form of interconnection of two subsystems by applying an input output method and a two-term approximation approach, which is employed to approximate the time-varying delay. Our attention is focused on the design of fuzzy fault detection filter (FFDF) such that, for all data missing conditions, and measurement quantization, the residual system is stochastically stable with a guaranteed H-infinity performance. Sufficient conditions are first established via introducing some slack matrices to facilitate the FDF design procedure by eliminating the coupling between the Lyapunov matrices and the system matrices. Numerical examples are provided to demonstrate the effectiveness and applicability of the proposed method. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文研究了带有量化和丢包的离散时间延迟模糊网络控制系统的故障检测(FD)问题。与现有的FD结果不同,所提出的结果针对闭环设计问题,即控制器增益和故障检测滤波器(FDF)增益同时设计。假定在量化器到FDF和控制器到物理设备的通信链路中发生丢失现象,其中丢包的丢失概率由单个随机二进制分布控制,而量化误差被视为扇区界不确定性。离散时间模糊网络系统首先通过应用输入输出方法和两项近似方法转换为两个子系统的互连形式,该方法用于近似时变延迟。我们的注意力集中在模糊故障检测滤波器(FFDF)的设计上,这样,对于所有数据丢失情况和测量量化,残差系统都是随机稳定的,并具有可保证的H无穷大性能。首先通过引入一些松弛矩阵来建立充分条件,以通过消除Lyapunov矩阵与系统矩阵之间的耦合来促进FDF设计过程。数值例子说明了该方法的有效性和适用性。 (C)2016 Elsevier B.V.保留所有权利。

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