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Autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control
Thesis (MEng)--Stellenbosch University, 2023.
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| Format: | Thesis |
| Language: | en_ZA en_ZA |
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Stellenbosch : Stellenbosch University
2023
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| _version_ | 1867613777738858496 |
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| access_status_str | Open Access |
| author | Louw, Ulrich |
| author2 | Jordaan, Willem |
| author_browse | Jordaan, Willem Louw, Ulrich |
| author_facet | Jordaan, Willem Louw, Ulrich |
| author_sort | Louw, Ulrich |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng)--Stellenbosch University, 2023. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/127178 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA en_ZA |
| last_indexed | 2026-06-10T12:41:32.562Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/127178 Autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control Louw, Ulrich Jordaan, Willem Schoeman, J. C. Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Autonomous Diagnosis;Satellite Sensor Anomalies; Ensure Fault Tolerant Control Satellite constellations Anomaly detection (Computer security) Satellite triangulation Thesis (MEng)--Stellenbosch University, 2023. ENGLISH ABSTRACT: Many satellites rely on attitude estimation algorithms to fuse information from multiple sensor sources. Some of these sensors might encounter false and erroneous measurements due to practical disturbances. In this thesis, methods are developed to increase the reliability of an extended Kalman filter when practical environmental anomalies occur. This is done by firstly detecting whether the current sensor measurements are anomalous and thereafter classifying the anomalous sensor. Different recovery methods are compared based on varying prediction accuracies. It was concluded that for prediction accuracies above 90%, the recovery technique that omits anomalous sensor measurements from the extended Kalman filter, is the best proposed recovery method. The random forest algorithm performs the best for isolating anomalies and using it separately or in conjunction with the local outlier factor algorithm for anomaly detection provide similar results. Implementing the local outlier factor algorithm increases the time efficiency. From simulations, it was found that a satellite attitude determination and control system that can predict and isolate practical anomalies improves the robustness and accuracy of the estimated attitude. AFRIKAANS OPSOMMING: Baie satelliete is afhanklik van ori¨entasie afskattings algoritmes om die informasie van verskeie sensore te vereenselwig. Sommige sensore kan vals of foutiewe lesings ervaar weens praktiese versteurings. In hierdie tesis word metodes ontwikkel wat die betroubaarheid van die uitgebreide Kalman filter vergroot wanneer praktiese omgewings versteurings voorkom. Dit word gedoen deur eerstens die sensor anomalie waar te neem en daarna die verantwoordelike sensor te klassifiseer. Verskeie regstellende metodes word vergelyk met ’n vari¨ende akkuraatheid. Die gevolgtrekking is dat vir akkuraathede bo 90% is die beste regstellende tegniek, die een wat slegs sensor afmetings verwyder van die Kalman filter se afmeting opdatering. Die lukrake woud algoritme is die beste isolasie metode en om dit te gebruik in samehorigheid met die lokale uitskietsel faktor algoritme vir anomalie waarneming of daarsonder produseer dieselfde resultate. Deur die lokale uitskietsel faktor algoritme te gebruik verhoog die tyd effektiwiteit van die stelsel. Deur die gebruik van simulasie is dit gevind dat ’n sisteem wat die praktiese anomalie¨e kan klassifiseer, verbeter die robustheid en akkuraatheid van die ori¨entasie afksatting. Masters 2023-03-03T11:32:22Z 2023-05-18T07:08:21Z 2023-03-03T11:32:22Z 2023-05-18T07:08:21Z 2023-03 Thesis http://hdl.handle.net/10019.1/127178 en_ZA en_ZA Stellenbosch University xi1, 134 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Autonomous Diagnosis;Satellite Sensor Anomalies; Ensure Fault Tolerant Control Satellite constellations Anomaly detection (Computer security) Satellite triangulation Louw, Ulrich Autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control |
| title | Autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control |
| title_full | Autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control |
| title_fullStr | Autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control |
| title_full_unstemmed | Autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control |
| title_short | Autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control |
| title_sort | autonomous diagnosis of satellite sensor anomalies to ensure fault tolerant control |
| topic | Autonomous Diagnosis;Satellite Sensor Anomalies; Ensure Fault Tolerant Control Satellite constellations Anomaly detection (Computer security) Satellite triangulation |
| url | http://hdl.handle.net/10019.1/127178 |
| work_keys_str_mv | AT louwulrich autonomousdiagnosisofsatellitesensoranomaliestoensurefaulttolerantcontrol |