Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm
Quadrotor unmanned aerial vehicle (UAV) has superior characteristics such as ability to take off and land vertically, to hover in a stable air condition and to perform fast maneuvers. However, developing a high-performance quadrotor UAV controller is a difficult problem as quadrotor is an unstable a...
Saved in:
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Institute of Advanced Engineering and Science
2020
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/93368/1/MohdAriffananMohdBasri2020_OptimalBacksteppingControlOfQuadrotorUAV.pdf http://eprints.utm.my/id/eprint/93368/ http://dx.doi.org/10.11591/eei.v9i5.2159 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.93368 |
---|---|
record_format |
eprints |
spelling |
my.utm.933682021-11-30T08:21:40Z http://eprints.utm.my/id/eprint/93368/ Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm Basri, M. A. Noordin, A. TK Electrical engineering. Electronics Nuclear engineering Quadrotor unmanned aerial vehicle (UAV) has superior characteristics such as ability to take off and land vertically, to hover in a stable air condition and to perform fast maneuvers. However, developing a high-performance quadrotor UAV controller is a difficult problem as quadrotor is an unstable and underactuated nonlinear system. The effort in this article focuses on designing and optimizing an autonomous quadrotor UAV controller. First, the aerial vehicle's dynamic model is presented. Then it is suggested an optimal backstepping controller (OBC). Traditionally, backstepping controller (BC) parameters are often selected arbitrarily. The gravitational search algorithm (GSA) is used here to determine the BC parameter optimum values. In the algorithm, the control parameters are calculated using an integral absolute error to minimize the fitness function. As the control law is based on the theorem of Lyapunov, the asymptotic stability of the scheme can be ensured. Finally, several simulation studies are conducted to show the efficacy of the suggested OBC. Institute of Advanced Engineering and Science 2020 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/93368/1/MohdAriffananMohdBasri2020_OptimalBacksteppingControlOfQuadrotorUAV.pdf Basri, M. A. and Noordin, A. (2020) Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm. Bulletin of Electrical Engineering and Informatics, 9 (5). pp. 1819-1826. ISSN 2089-3191 http://dx.doi.org/10.11591/eei.v9i5.2159 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
language |
English |
topic |
TK Electrical engineering. Electronics Nuclear engineering |
spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering Basri, M. A. Noordin, A. Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm |
description |
Quadrotor unmanned aerial vehicle (UAV) has superior characteristics such as ability to take off and land vertically, to hover in a stable air condition and to perform fast maneuvers. However, developing a high-performance quadrotor UAV controller is a difficult problem as quadrotor is an unstable and underactuated nonlinear system. The effort in this article focuses on designing and optimizing an autonomous quadrotor UAV controller. First, the aerial vehicle's dynamic model is presented. Then it is suggested an optimal backstepping controller (OBC). Traditionally, backstepping controller (BC) parameters are often selected arbitrarily. The gravitational search algorithm (GSA) is used here to determine the BC parameter optimum values. In the algorithm, the control parameters are calculated using an integral absolute error to minimize the fitness function. As the control law is based on the theorem of Lyapunov, the asymptotic stability of the scheme can be ensured. Finally, several simulation studies are conducted to show the efficacy of the suggested OBC. |
format |
Article |
author |
Basri, M. A. Noordin, A. |
author_facet |
Basri, M. A. Noordin, A. |
author_sort |
Basri, M. A. |
title |
Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm |
title_short |
Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm |
title_full |
Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm |
title_fullStr |
Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm |
title_full_unstemmed |
Optimal backstepping control of quadrotor UAV using gravitational search optimization algorithm |
title_sort |
optimal backstepping control of quadrotor uav using gravitational search optimization algorithm |
publisher |
Institute of Advanced Engineering and Science |
publishDate |
2020 |
url |
http://eprints.utm.my/id/eprint/93368/1/MohdAriffananMohdBasri2020_OptimalBacksteppingControlOfQuadrotorUAV.pdf http://eprints.utm.my/id/eprint/93368/ http://dx.doi.org/10.11591/eei.v9i5.2159 |
_version_ |
1718926057909780480 |
score |
13.209306 |