Model-based fault detection for the DELFI-N3XT attitude determination system

Napoleon E. Cornejo; Rouzbeh Amini; Georgi Gaydadjiev

doi:10.1109/AERO.2010.5446801

Model-based fault detection for the DELFI-N3XT attitude determination system

Napoleon E. Cornejo, Rouzbeh Amini, Georgi Gaydadjiev

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

8 Citations (Scopus)

Abstract

The Delfi-n3Xt nanosatellite is the second Dutch university satellite currently being developed at the Delft University of Technology. In its design, the Attitude Determination System (ADS) will be pivotal for optimal power point tracking to adequately provide the energy needed for normal operation and charging of the batteries. In this paper we explore a fault detection mechanism for the ADS based on the Unscented Kalman Filter (UKF) state estimator which has been successfully integrated into the simulation and modelling environment. The UKF provides a more computationally efficient estimator than traditional Kalman Filter variants. Faults introduced in the system include changes in the noise model and stuck-at-0 faults, resulting in disturbances in the output of the filter. Parameters of the filter are varied and the behaviour of the outcoming residuals is analyzed to evaluate its effectiveness in the detection of these errors.

Original language	English
Title of host publication	2010 IEEE Aerospace Conference Proceedings
Publisher	IEEE
ISBN (Print)	9781424438884
DOIs	https://doi.org/10.1109/AERO.2010.5446801
Publication status	Published - 2-Jun-2010
Externally published	Yes
Event	2010 IEEE Aerospace Conference - Big Sky, MT, United States Duration: 6-Mar-2010 → 13-Mar-2010

Publication series

Name	IEEE Aerospace Conference Proceedings
ISSN (Print)	1095-323X

Conference

Conference	2010 IEEE Aerospace Conference
Country	United States
City	Big Sky, MT
Period	06/03/2010 → 13/03/2010

Access to Document

10.1109/AERO.2010.5446801

Embargoed Document

Model-Based Fault Detection for the DELFI-N3XTAttitudeDetermination System
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Cite this

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title = "Model-based fault detection for the DELFI-N3XT attitude determination system",

abstract = "The Delfi-n3Xt nanosatellite is the second Dutch university satellite currently being developed at the Delft University of Technology. In its design, the Attitude Determination System (ADS) will be pivotal for optimal power point tracking to adequately provide the energy needed for normal operation and charging of the batteries. In this paper we explore a fault detection mechanism for the ADS based on the Unscented Kalman Filter (UKF) state estimator which has been successfully integrated into the simulation and modelling environment. The UKF provides a more computationally efficient estimator than traditional Kalman Filter variants. Faults introduced in the system include changes in the noise model and stuck-at-0 faults, resulting in disturbances in the output of the filter. Parameters of the filter are varied and the behaviour of the outcoming residuals is analyzed to evaluate its effectiveness in the detection of these errors.",

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