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Distributed non-fragile filtering for T-S fuzzy systems with event-based communications

机译:基于事件通信的T-S模糊系统的分布式非脆弱性过滤

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This paper is concerned with the distributed non-fragile filtering for a class of discrete-time Takagi-Sugeno (T-S) fuzzy systems with event-based communication. Firstly, for the purpose of reducing communication, a general event generator is employed for sensors to determine the event time instant and then broadcast the measurement output to the filters. Each sensor node is capable to make its own decision to broadcast the current measurement only when its local measurement output error exceeds a specified threshold. Secondly, filter gain variation phenomenon reflecting the filter implementation uncertainties is also taken into account as the sensor networks are prone to uncertain disturbance in their application. A unified modeling is proposed to capture the event-based communication, packet dropouts and filter gain variations, which approximates the practical sensor network more closely. Based on the fuzzy Lyapunov functional, sufficient conditions have been presented such that the filtering error system is asymptotically stable with a prescribed weighted disturbance attenuation level. The filter gain parameters are determined by solving an optimization problem. Finally, a simulation study is given to show the effectiveness of the proposed new design. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文涉及基于事件通信的一类离散时间Takagi-Sugeno(T-S)模糊系统的分布式非脆弱滤波。首先,出于减少通信的目的,将通用事件生成器用于传感器以确定事件时刻,然后将测量输出广播到滤波器。每个传感器节点仅在其本地测量输出误差超过指定阈值时才能够做出自己的决定,以广播当前测量。其次,由于传感器网络在其应用中容易受到不确定干扰,因此还考虑了反映滤波器实现不确定性的滤波器增益变化现象。提出了一个统一的模型来捕获基于事件的通信,数据包丢失和滤波器增益变化,从而更接近实际的传感器网络。基于模糊Lyapunov函数,已经给出了充分的条件,使得滤波误差系统在规定的加权干扰衰减水平下渐近稳定。通过解决优化问题来确定滤波器增益参数。最后,仿真研究表明了所提出的新设计的有效性。 (C)2016 Elsevier B.V.保留所有权利。

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