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DC Field | Value | Language |
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dc.date.accessioned | 2022-05-17T09:23:33Z | - |
dc.date.available | 2022-05-17T09:23:33Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Scerri, M. (2010). Aircraft autoland system using fuzzy logic (Bachelor's dissertation). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/95804 | - |
dc.description | B.Sc. IT (Hons)(Melit.) | en_GB |
dc.description.abstract | A full aircraft Autoland system using fuzzy logic has been developed. It is based on the flight model of a medium sized commercial airliner (Boeing 73 7-800), and was designed for a full 6 degree of freedom flight simulator. This was achieved by implementing several independent single output Fuzzy Controllers that are able to work together based on instrument readings continuously taken from the aircraft. Scenarios the solution was tested in include varying glidepath angles, various weather situations that include severe stable crosswinds and severe gusting crosswinds. For each case, the final results show that not only were safe landings performed in cases where the conditions were within the limitations set by the aircraft's manufacturer but also in worse conditions. These include landing in airports with a steep glidepath angle (such as London City Airport) but also landing in extreme crosswind conditions nearly double that of what the manufacturers recommend is used as a limitation. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Fuzzy systems | en_GB |
dc.subject | Nautical instruments | en_GB |
dc.subject | Artificial intelligence | en_GB |
dc.title | Aircraft autoland system using fuzzy logic | en_GB |
dc.type | bachelorThesis | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Information and Communication Technology. Department of Artificial Intelligence | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Scerri, Matthew (2010) | - |
Appears in Collections: | Dissertations - FacICT - 2010 Dissertations - FacICTAI - 2002-2014 |
Files in This Item:
File | Description | Size | Format | |
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BSC(HONS)IT_Scerri_Matthew_2010.pdf Restricted Access | 10.3 MB | Adobe PDF | View/Open Request a copy |
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