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Model Based Fault Diagnosis of Low Earth Orbiting (LEO) Satellite using Spherical Unscented Kalman Filter

机译:基于模型的基于模型使用球形无需Kalman滤波器的低地球轨道(LEO)卫星的故障诊断

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Model based fault detection and diagnosis (FDD) using a non-linear estimation technique is presented here. The non-linear estimation technique namely spherical Unscented Kalman Filter (UKF) has been applied to other kinds of estimation problems but has never been applied to the FDD problem of a Low Earth Orbiting (LEO) satellite. It has been shown in this work that compared to the standard UKF, which is a derivative free estimation technique unlike the popular Extended Kalman Filter (EKF), the spherical UKF can perform better in terms of computational savings without sacrificing accuracy. Hence it is better suited for real-time fault diagnosis. A planar model of the satellite is used to demonstrate the technique.
机译:此处提出了使用非线性估计技术的基于模型的故障检测和诊断(FDD)。非线性估计技术即球形无需卡尔曼滤波器(UKF)已经应用于其他类型的估计问题,但从未应用于低地球轨道(Leo)卫星的FDD问题。它已在这项工作中显示,与标准UKF相比,这是一种与流行的扩展卡尔曼滤波器(EKF)不同的衍生免费估计技术,球面UKF可以在不牺牲准确度的情况下在计算节省方面更好地表现更好。因此,它更适合实时故障诊断。卫星的平面模型用于展示该技术。

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