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首页> 外文期刊>International journal of systems science >Distributed H_∞ filter design for T-S fuzzy systems with Sigma-Delta quantisation via non-PDC scheme
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Distributed H_∞ filter design for T-S fuzzy systems with Sigma-Delta quantisation via non-PDC scheme

机译:具有非PDC方案的Sigma-Delta量化的T-S模糊系统的分布式H_∞过滤器设计

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The paper focuses on the distributed filtering problem over wireless sensor networks (WSNs) for a class of discrete-time T-S fuzzy systems with immeasurable premise variables and Sigma-Delta quantiser. Two defectives are considered including packet losses and multiplicative noises, which can be represented by some mutual independent random variables, respectively. Unlike conventional logarithmic quantiser, by utilising the Sigma-Delta dynamic quantiser, the quantised measurement outputs are broadcasted to the distributed filters over WSNs, only requiring a finite number of quantisation levels, and the static errors can be eliminated simultaneously. Using non-PDC scheme, an estimated premise variable-dependent distributed filter is designed over WSNs. Then treating the premise variables as uncertainties, a robust distributed filtering problem is considered for such an uncertain filtering error system. Based on the fuzzy Lyapunov function, the less conservative mean-square stable conditions with a prescribed performance index for the uncertain filtering error dynamical systems are presented. The filter parameters are determined by solving a set of linear matrix inequalities (LMIs). Finally, a tunnel diode circuit model and a numerical example are presented to illustrate the theoretical findings.
机译:本文侧重于无线传感器网络(WSNS)的分布式滤波问题,用于一类具有无法估量的前提变量和Sigma-Delta量化器的一类离散时间T-S模糊系统。两种缺陷被认为包括分组丢失和乘法噪声,其可以分别由一些相互独立的随机变量表示。与传统的对数水解器不同,通过利用Sigma-Delta动态量化器,将量化的测量输出广播到WSN上的分布式滤波器,仅需要有限数量的量化级别,并且可以同时消除静态错误。使用非PDC方案,设计了估计的前提变量依赖性分布式滤波器以通过WSN设计。然后将前提变量视为不确定因素,考虑了一种强大的分布式过滤问题,用于这种不确定的滤波误差系统。基于模糊Lyapunov功能,提出了较少保守的平均方形稳定条件,具有不确定的过滤误差动态系统的规定性能指标。通过求解一组线性矩阵不等式(LMI)来确定滤波器参数。最后,提出了一种隧道二极管电路模型和数值示例以说明理论上的发现。

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