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Memory scheduling robust H∞ filter-based fault detection for discrete-time polytopic uncertain systems over fading channels

机译:基于存储器调度的基于鲁棒H∞滤波的离散时间多变量不确定系统故障检测

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摘要

A novel memory scheduling robust H∞ fault detection filter (FDF) is proposed for a class of discrete-time polytopic uncertain systems with fading channel communication networks. The main merit of this filter-based fault detection method is that it can significantly improve the robustness of FDF to attenuate influences from external disturbance, channel fading and model uncertainty on fault detection accuracy. Designing such FDF involves three main stages. First of all, a memory scheduling FDF structure is proposed based on the utilisation of weighted historical filter's states over interval instants, and a residual error system is formulated based on time partition and state augmented approaches. Then, the parameter-dependent Lyapunov method is further utilised to analyse the stochastic stability of the residual error system with the help of Finsler equivalent transformation. In the following, a two-stage optimisation algorithm combined with scalar parameters method is constructed to design memory scheduling FDF in a less conservative linear matrix inequality manner. Finally, a random numerical verification with 300 test systems and a case study of an industrial continuous-stirred tank reactor are exploited to show the effectiveness of obtained results.
机译:针对一类具有衰落信道通信网络的离散时间多主题不确定系统,提出了一种新颖的存储调度鲁棒H∞故障检测滤波器。这种基于滤波器的故障检测方法的主要优点在于,它可以显着提高FDF的鲁棒性,以减弱外部干扰,通道衰落和模型不确定性对故障检测精度的影响。设计这样的FDF涉及三个主要阶段。首先,基于时间间隔加权历史滤波器状态的利用,提出了一种内存调度FDF结构,并基于时间划分和状态增强方法建立了残差系统。然后,在Finsler等效变换的帮助下,进一步利用参数依赖的Lyapunov方法分析残差系统的随机稳定性。接下来,构造一个两阶段优化算法,结合标量参数方法,以一种不太保守的线性矩阵不等式方式设计内存调度FDF。最后,利用300个测试系统进行的随机数值验证以及工业连续搅拌釜反应器的案例研究证明了所获得结果的有效性。

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