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Fault Diagnosis and Fault Tolerant Control for Non-Gaussian Time-delayed Singular Stochastic Distribution Systems

机译:非高斯时滞奇异随机分布系统的故障诊断与容错控制

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摘要

Stochastic distribution control (SDC) is a new branch of stochastic system control that the system output is the probability density function (PDF) of the output. In practice, some algebraic relations exist between the input and the weights of SDC systems, leading to a singular state space model between the weights and the control input which increases the complexity of the system. The ignorance of time delay in practical systems will make the effectiveness of the fault diagnosis (FD) and fault tolerant control (FTC) be reduced. In this paper, the linear B-spline basis functions are used to approximate the output PDF. A FD approach based on the adaptive observer is established to diagnose the size of fault in the singular time-delayed SDC system. With the fault diagnosis information, a fault tolerant controller based on PI tracking control scheme is constructed to make the post-fault PDF still track the given distribution.. The post-fault closed-loop stability analysis with the practical fault tolerant controller is carried out based on the Lyapunov stability theorem. Finally, a numerical simulation is provided to demonstrate the effectiveness of the proposed approach.
机译:随机分布控制(SDC)是随机系统控制的新分支,系统输出是输出的概率密度函数(PDF)。在实践中,SDC系统的输入和权重之间存在一些代数关系,导致权重和控制输入之间存在奇异的状态空间模型,这增加了系统的复杂性。实际系统中时间延迟的无知将降低故障诊断(FD)和容错控制(FTC)的效率。在本文中,线性B样条基函数用于近似输出PDF。建立了基于自适应观测器的FD方法,以诊断奇异时滞SDC系统中的故障大小。利用故障诊断信息,构造了基于PI跟踪控制方案的容错控制器,以使故障后PDF仍能跟踪给定的分布。利用实用的容错控制器进行了故障后闭环稳定性分析。基于Lyapunov稳定性定理。最后,提供了数值模拟,以证明所提出方法的有效性。

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