Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle

Quadrotor unmanned aerial vehicle (UAV) is an underactuated multi-input and multi-output (MIMO) system which has nonlinear dynamic behavior such as high coupling degree and unknown nonlinearities. It is a great challenge to design a quadrotor control system due to these features. In this paper, the...

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Main Authors: Mohd. Basri, Mohd. Ariffanan, Husain, Abdul Rashid, Danapalasingam, Kumeresan A.
Format: Article
Published: Kluwer Academic Publishers 2015
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Online Access:http://eprints.utm.my/id/eprint/55004/
http://dx.doi.org/10.1007/s10846-014-0072-3
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spelling my.utm.550042017-02-15T07:16:37Z http://eprints.utm.my/id/eprint/55004/ Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle Mohd. Basri, Mohd. Ariffanan Husain, Abdul Rashid Danapalasingam, Kumeresan A. TK Electrical engineering. Electronics Nuclear engineering Quadrotor unmanned aerial vehicle (UAV) is an underactuated multi-input and multi-output (MIMO) system which has nonlinear dynamic behavior such as high coupling degree and unknown nonlinearities. It is a great challenge to design a quadrotor control system due to these features. In this paper, the contribution is focused on the backstepping-based robust control design of the quadrotor UAV. Firstly, the dynamic model of the aerial vehicle is mathematically formulated. Then, a robust controller is designed for the stabilization and tracking control of the vehicle. The developed robust control system comprises a backstepping and a proportional-derivative (PD) controller. Backstepping is a recursive design methodology that uses Lyapunov theorem which can guarantee the stability of the nominal model system, while PD control is used to attenuate the effects caused by system uncertainties. For the problem of determining the backstepping control parameters, particle swarm optimization (PSO) algorithm has been employed. In addition, the genetic algorithm (GA) technique is also adopted for the purpose of performance comparison with PSO scheme. Finally, the designed controller is experimentally evaluated on a quadrotor simulation environment to demonstrate the effectiveness and merits of the theoretical development. Kluwer Academic Publishers 2015-08 Article PeerReviewed Mohd. Basri, Mohd. Ariffanan and Husain, Abdul Rashid and Danapalasingam, Kumeresan A. (2015) Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle. Journal of Intelligent and Robotic Systems: Theory and Applications, 79 (2). pp. 295-321. ISSN 0921-0296 http://dx.doi.org/10.1007/s10846-014-0072-3 DOI:10.1007/s10846-014-0072-3
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/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohd. Basri, Mohd. Ariffanan
Husain, Abdul Rashid
Danapalasingam, Kumeresan A.
Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle
description Quadrotor unmanned aerial vehicle (UAV) is an underactuated multi-input and multi-output (MIMO) system which has nonlinear dynamic behavior such as high coupling degree and unknown nonlinearities. It is a great challenge to design a quadrotor control system due to these features. In this paper, the contribution is focused on the backstepping-based robust control design of the quadrotor UAV. Firstly, the dynamic model of the aerial vehicle is mathematically formulated. Then, a robust controller is designed for the stabilization and tracking control of the vehicle. The developed robust control system comprises a backstepping and a proportional-derivative (PD) controller. Backstepping is a recursive design methodology that uses Lyapunov theorem which can guarantee the stability of the nominal model system, while PD control is used to attenuate the effects caused by system uncertainties. For the problem of determining the backstepping control parameters, particle swarm optimization (PSO) algorithm has been employed. In addition, the genetic algorithm (GA) technique is also adopted for the purpose of performance comparison with PSO scheme. Finally, the designed controller is experimentally evaluated on a quadrotor simulation environment to demonstrate the effectiveness and merits of the theoretical development.
format Article
author Mohd. Basri, Mohd. Ariffanan
Husain, Abdul Rashid
Danapalasingam, Kumeresan A.
author_facet Mohd. Basri, Mohd. Ariffanan
Husain, Abdul Rashid
Danapalasingam, Kumeresan A.
author_sort Mohd. Basri, Mohd. Ariffanan
title Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle
title_short Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle
title_full Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle
title_fullStr Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle
title_full_unstemmed Enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle
title_sort enhanced backstepping controller design with application to autonomous quadrotor unmanned aerial vehicle
publisher Kluwer Academic Publishers
publishDate 2015
url http://eprints.utm.my/id/eprint/55004/
http://dx.doi.org/10.1007/s10846-014-0072-3
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score 13.211869