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Online Parameter Estimation of an Ag...

Wright, Henry.

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Online Parameter Estimation of an Agile Unmanned Aerial Vehicle.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Online Parameter Estimation of an Agile Unmanned Aerial Vehicle./
Author:	Wright, Henry.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	120 p.
Notes:	Source: Masters Abstracts International, Volume: 84-11.
Contained By:	Masters Abstracts International84-11.
Subject:	Aerospace engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30311328
ISBN:	9798379545079

Online Parameter Estimation of an Agile Unmanned Aerial Vehicle.
Wright, Henry.

Online Parameter Estimation of an Agile Unmanned Aerial Vehicle. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 120 p.

Source: Masters Abstracts International, Volume: 84-11.

Thesis (M.S.)--Saint Louis University, 2023.

This item must not be sold to any third party vendors.

This study investigates the design, development, and testing of a framework to estimate the short-period stability and control derivatives online for an agile unmanned aerial system. With the increased use of autonomous aerial systems in industry for tasks such as package delivery, search and rescue, and reconnaissance, the nature of autonomous flight is poised to change forever. Autonomous platforms applicable to these industries implement modern and classical control methods to command position, orientation, maintain stability, and complete a mission at a variety of flight conditions. Issues of safety and mission viability can arise when these systems encounter changing dynamics or flight conditions that were not considered during the control design. Structural damage, changing environmental conditions, and sensor failures can potentially push the controller into failure, resulting in damages to people or infrastructure. Before the full benefits of these autonomous platforms can be realized, the systems used must be able to estimate the vehicle model online and in real-time, identify any unexpected changing dynamics or failures, and augment the controller to compensate for them to maintain safety and stability.Using a small, agile RC aircraft, an off-the-shelf autonomous flight controller, an on-board companion computer, and a custom designed air-data acquisition system, flight tests were performed for the purpose of estimating the relevant short-period parameters at four different angles-of-attack (? = 2°,4°,6°,8°). During flight and after exciting the short-period dynamic mode at each flight condition, online parameter estimates were calculated using a sequential least-squares methodology in the frequency domain. Simulations of the short period dynamics were run on validation data sets and the results compared to those produced offline and off-board using traditional least-squares approach in the time-domain, a maximum likelihood estimator (MLE), and a commercially available software (Advanced Aircraft Analysis).Results from this effort indicate that the online estimates under-performed at estimating the responses of the validation data sets as compared to those produced from the off-board methodologies. Among the offline methods, the maximum likelihood estimator out-performed all other methodologies. It was also found that some of the estimates (???, ????) produced from the maximum likelihood estimator and online estimates showed discrepancies in their sign compared to expected signs following standard aircraft conventions. This could potentially be attributed to the fact that that maintaining the small perturbation dynamics about a desired trim flight condition after performing excitation is a difficult task owing to the test platform's low weight, low moments-of-inertia, and high airspeed. Although the online parameter estimation framework that was designed functioned properly, it was concluded that further improvements to the onboard hardware and software would need to be made to improve parameter estimation results for high agility UAV platforms.

ISBN: 9798379545079Subjects--Topical Terms:

1002622
Aerospace engineering.
Subjects--Index Terms:

Online

Online Parameter Estimation of an Agile Unmanned Aerial Vehicle.
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300 $a 120 p.
500 $a Source: Masters Abstracts International, Volume: 84-11.
500 $a Advisor: Gururajan, Srikanth.
502 $a Thesis (M.S.)--Saint Louis University, 2023.
506 $a This item must not be sold to any third party vendors.
520 $a This study investigates the design, development, and testing of a framework to estimate the short-period stability and control derivatives online for an agile unmanned aerial system. With the increased use of autonomous aerial systems in industry for tasks such as package delivery, search and rescue, and reconnaissance, the nature of autonomous flight is poised to change forever. Autonomous platforms applicable to these industries implement modern and classical control methods to command position, orientation, maintain stability, and complete a mission at a variety of flight conditions. Issues of safety and mission viability can arise when these systems encounter changing dynamics or flight conditions that were not considered during the control design. Structural damage, changing environmental conditions, and sensor failures can potentially push the controller into failure, resulting in damages to people or infrastructure. Before the full benefits of these autonomous platforms can be realized, the systems used must be able to estimate the vehicle model online and in real-time, identify any unexpected changing dynamics or failures, and augment the controller to compensate for them to maintain safety and stability.Using a small, agile RC aircraft, an off-the-shelf autonomous flight controller, an on-board companion computer, and a custom designed air-data acquisition system, flight tests were performed for the purpose of estimating the relevant short-period parameters at four different angles-of-attack (? = 2°,4°,6°,8°). During flight and after exciting the short-period dynamic mode at each flight condition, online parameter estimates were calculated using a sequential least-squares methodology in the frequency domain. Simulations of the short period dynamics were run on validation data sets and the results compared to those produced offline and off-board using traditional least-squares approach in the time-domain, a maximum likelihood estimator (MLE), and a commercially available software (Advanced Aircraft Analysis).Results from this effort indicate that the online estimates under-performed at estimating the responses of the validation data sets as compared to those produced from the off-board methodologies. Among the offline methods, the maximum likelihood estimator out-performed all other methodologies. It was also found that some of the estimates (???, ????) produced from the maximum likelihood estimator and online estimates showed discrepancies in their sign compared to expected signs following standard aircraft conventions. This could potentially be attributed to the fact that that maintaining the small perturbation dynamics about a desired trim flight condition after performing excitation is a difficult task owing to the test platform's low weight, low moments-of-inertia, and high airspeed. Although the online parameter estimation framework that was designed functioned properly, it was concluded that further improvements to the onboard hardware and software would need to be made to improve parameter estimation results for high agility UAV platforms.
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650 4 $a Aerospace engineering. $3 1002622
650 4 $a Mechanics. $3 525881
653 $a Online
653 $a Parameter estimation
653 $a Pixhawk
653 $a Unmanned aerial vehicles
690 $a 0538
690 $a 0346
710 2 $a Saint Louis University. $b Engineering. $3 2099350
773 0 $t Masters Abstracts International $g 84-11.
790 $a 0193
791 $a M.S.
792 $a 2023
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30311328