基于GP-EKF和GP-UKF算法的非线性系统故障检测

B. Safarinejadian, Elham Kowsari
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引用次数: 29

摘要

本文提出了两种新的非线性系统故障检测方法。所提出的方法是将扩展卡尔曼滤波器(EKF)和无气味卡尔曼滤波器(UKF)与高斯过程(GPs)相结合。这些算法的一个主要优点是不需要系统的模型,同时在故障检测方面具有准确和快速的特点。为了证明所提算法的良好性能,将其应用于具有高度非线性动力学的飞机跟踪系统。仿真结果表明,GP-UKF算法在故障检测方面优于GP-EKF算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault detection in non-linear systems based on GP-EKF and GP-UKF algorithms
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.
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