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Fault diagnosis and fault tolerant control for non-Gaussian singular stochastic distribution systems

机译:非高斯奇异随机分布系统的故障诊断和容错控制

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This paper presents new fault detection and diagnosis (FDD) and fault tolerant control (FTC)algorithms for non-Gaussian singular stochastic distribution control (SDC) systems. Different from general SDC systems, in singular SDC systems, the relationship between the weights and the control input is expressed by a singular state space mode, which increases the difficulty in the FDD and FDD design. The FDD algorithm is formulated by extending the developed FDD algorithms of non-singular SDC systems to singular systems. Based on the estimated fault information, the fault tolerant controller can be designed to make the post-fault probability density function (PDF) still track the given distribution. Computer simulations are given to show the effectiveness of the proposed FDD and FTC algorithms.
机译:本文为非高斯奇异随机分布控制(SDC)系统提出了新的故障检测与诊断(FDD)和容错控制(FTC)算法。与一般的SDC系统不同,在奇异的SDC系统中,权重和控制输入之间的关系由奇异的状态空间模式表示,这增加了FDD和FDD设计的难度。通过将已开发的非奇异SDC系统的FDD算法扩展到奇异系统来制定FDD算法。基于估计的故障信息,可以将容错控制器设计为使故障后概率密度函数(PDF)仍然跟踪给定的分布。计算机仿真表明了所提出的FDD和FTC算法的有效性。

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