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Fault detection in non-linear systems based on GP-EKF and GP-UKF algorithms

机译:基于GP-EKF和GP-UKF算法的非线性系统故障检测

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In this paper, two new fault detection methods are proposed for non-linear systems. The proposed methods are based on combining an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) with Gaussian processes (GPs). One of the major advantages of these algorithms is that they do not need the system's model while they have an accurate and fast operation in fault detection. In order to show the promising performance of the proposed algorithms, they are applied to an aeroplane tracking system with a highly non-linear dynamics. Superiority of the GP-UKF over GP-EKF in fault detection is also shown based on the simulation results.
机译:本文针对非线性系统提出了两种新的故障检测方法。所提出的方法是基于将扩展卡尔曼滤波器(EKF)和无味卡尔曼滤波器(UKF)与高斯过程(GPs)结合在一起的。这些算法的主要优点之一是,它们在故障检测中具有准确而快速的操作,因此不需要系统模型。为了显示所提出算法的有希望的性能,将它们应用于具有高度非线性动力学的飞机跟踪系统。根据仿真结果,还显示了GP-UKF在故障检测方面优于GP-EKF的优势。

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