Publication Type:

Journal Article

Source:

IFAC-PapersOnLine, Elsevier, Volume 49, Number 1, p.635-638 (2016)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84974644196&partnerID=40&md5=efd08c2ec66227c5bcce6c362e48810b

Keywords:

Bandpass filters, Computational savings, Estimation, Estimation techniques, Extended Kalman filters, Failure analysis, Fault detection, filtration, Kalman filters, LEO satellite, Linear systems, Low earth orbiting satellites, Model-based fault detection, Model-based fault diagnosis, Nonlinear filtering, Orbits, Real-time fault diagnosis, Satellites, Spheres, Spherical unscented Kalman filter

Abstract:

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. © 2016 IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Notes:

cited By 0

Cite this Research Publication

P. V. Sunil Nag, Silla, G. K., Gummadi, V. H. V., Harishankar, C. B., Ray, V. K., and Dr. Santhosh Kumar C., “Model Based Fault Diagnosis Of Low Earth Orbiting (LEO) Satellite Using Spherical Unscented Kalman Filter”, IFAC-PapersOnLine, vol. 49, pp. 635-638, 2016.

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