Autonomous controller for unmanned aerial vehicle

The Unmanned Aerial Vehicle (UAV) is one of the technologies that is constantly evolving in order to be implemented for more applications. In the past, it is only used for military application for combat purposes, where the UAV will carry aircraft ordnance such as missiles for air strikes. As the te...

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Main Author: Tan, Beng Yew
Other Authors: Mahardhika Pratama
Format: Final Year Project
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/78985
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-789852023-03-03T20:52:50Z Autonomous controller for unmanned aerial vehicle Tan, Beng Yew Mahardhika Pratama School of Computer Science and Engineering Engineering::Computer science and engineering The Unmanned Aerial Vehicle (UAV) is one of the technologies that is constantly evolving in order to be implemented for more applications. In the past, it is only used for military application for combat purposes, where the UAV will carry aircraft ordnance such as missiles for air strikes. As the technology for UAV advances and the cost of development reduces, it becomes a technology that is readily available for the common people. Now, UAV can be applied in more areas, such as photography, delivery and critical missions such as Search & Rescue. One of the techniques to further improve the performance and utility of UAV is to automize it and giving it the ability to operate on its own. While research has been done on the potential for autonomous UAV, the challenge has been to provide a stable and consistent controller for it. Due to the complexity of the hardware of UAV and the directions that it is required to operate on, it is difficult and time consuming to tune and optimize the UAV to operate perfectly under every condition. This project explores the performance of Parsimonious Automatic Controller (PAC) when implemented on an autonomous UAV and compares the result with the commonly used linear Proportional-Integral-Derivative (PID) controller. With the application of machine learning implemented into PAC, it reduces the parameters that is required while improving the performance of the controller in the process. By testing and simulating the use of this controller onto the autonomous UAV, it determines the viability of implementing the UAV for real-world missions. It also opens the possibility of implementing it on other platforms or systems and potential improving the performance of it. Bachelor of Engineering (Computer Engineering) 2019-11-18T08:55:31Z 2019-11-18T08:55:31Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/78985 en Nanyang Technological University 51 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Tan, Beng Yew
Autonomous controller for unmanned aerial vehicle
description The Unmanned Aerial Vehicle (UAV) is one of the technologies that is constantly evolving in order to be implemented for more applications. In the past, it is only used for military application for combat purposes, where the UAV will carry aircraft ordnance such as missiles for air strikes. As the technology for UAV advances and the cost of development reduces, it becomes a technology that is readily available for the common people. Now, UAV can be applied in more areas, such as photography, delivery and critical missions such as Search & Rescue. One of the techniques to further improve the performance and utility of UAV is to automize it and giving it the ability to operate on its own. While research has been done on the potential for autonomous UAV, the challenge has been to provide a stable and consistent controller for it. Due to the complexity of the hardware of UAV and the directions that it is required to operate on, it is difficult and time consuming to tune and optimize the UAV to operate perfectly under every condition. This project explores the performance of Parsimonious Automatic Controller (PAC) when implemented on an autonomous UAV and compares the result with the commonly used linear Proportional-Integral-Derivative (PID) controller. With the application of machine learning implemented into PAC, it reduces the parameters that is required while improving the performance of the controller in the process. By testing and simulating the use of this controller onto the autonomous UAV, it determines the viability of implementing the UAV for real-world missions. It also opens the possibility of implementing it on other platforms or systems and potential improving the performance of it.
author2 Mahardhika Pratama
author_facet Mahardhika Pratama
Tan, Beng Yew
format Final Year Project
author Tan, Beng Yew
author_sort Tan, Beng Yew
title Autonomous controller for unmanned aerial vehicle
title_short Autonomous controller for unmanned aerial vehicle
title_full Autonomous controller for unmanned aerial vehicle
title_fullStr Autonomous controller for unmanned aerial vehicle
title_full_unstemmed Autonomous controller for unmanned aerial vehicle
title_sort autonomous controller for unmanned aerial vehicle
publishDate 2019
url http://hdl.handle.net/10356/78985
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