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Fault Detection and Emergency Path Planning for Fixed Wing UAVs.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Fault Detection and Emergency Path Planning for Fixed Wing UAVs./
作者:	Gomez Quezada, Ruth.
面頁冊數:	1 online resource (54 pages)
附註:	Source: Masters Abstracts International, Volume: 85-04.
Contained By:	Masters Abstracts International85-04.
標題:	Engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9798380591140

Fault Detection and Emergency Path Planning for Fixed Wing UAVs.
Gomez Quezada, Ruth.

Fault Detection and Emergency Path Planning for Fixed Wing UAVs. - 1 online resource (54 pages)

Source: Masters Abstracts International, Volume: 85-04.

Thesis (M.S.)--University of Maryland, College Park, 2023.

Includes bibliographical references

The implementation of Uncrewed Aerial Vehicles (UAVs) for civilian and military purposes requires safety protocols. Control surface failures are among the most common issues in fixed-wing UAVs. This study presents two heuristic-based algorithms developed to detect such faults. The Mahalanobis Distance Fault Detection Algorithm (MDFDA) employs the Mahalanobis distance to identify anomalies in UAV states. On the other hand, the Fuzzy Logic Fault Detection Algorithm (FLFDA) uses fuzzy logic to identify jammed control surfaces. In the event of a fault, an emergency path planning algorithm is initiated. This algorithm leverages terrain and population data to pinpoint safe landing zones. However, the type of fault the system encounters will impact the aircraft's ability to reach these safe zones. In this study, unreachable zones are delineated based on the specific control surface fault detected. These zones are areas where the aircraft cannot land or traverse due to the fault. By employing the proposed protocol, the aircraft can detect a fault during mid-flight, select a safe landing zone within its reachable range, and mitigate the effects of the control surface fault. This approach enhances the chances of preserving the aircraft and ensures the safety of the surrounding population.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380591140Subjects--Topical Terms:

561152
Engineering.
Subjects--Index Terms:

Emergency path planningIndex Terms--Genre/Form:

554714
Electronic books.

Fault Detection and Emergency Path Planning for Fixed Wing UAVs.
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520 $a The implementation of Uncrewed Aerial Vehicles (UAVs) for civilian and military purposes requires safety protocols. Control surface failures are among the most common issues in fixed-wing UAVs. This study presents two heuristic-based algorithms developed to detect such faults. The Mahalanobis Distance Fault Detection Algorithm (MDFDA) employs the Mahalanobis distance to identify anomalies in UAV states. On the other hand, the Fuzzy Logic Fault Detection Algorithm (FLFDA) uses fuzzy logic to identify jammed control surfaces. In the event of a fault, an emergency path planning algorithm is initiated. This algorithm leverages terrain and population data to pinpoint safe landing zones. However, the type of fault the system encounters will impact the aircraft's ability to reach these safe zones. In this study, unreachable zones are delineated based on the specific control surface fault detected. These zones are areas where the aircraft cannot land or traverse due to the fault. By employing the proposed protocol, the aircraft can detect a fault during mid-flight, select a safe landing zone within its reachable range, and mitigate the effects of the control surface fault. This approach enhances the chances of preserving the aircraft and ensures the safety of the surrounding population.
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