Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network

In this paper, adaptive tracking control is applied to improve performances of an underactuated quadrotor helicopter with respect to attitude and position control. Firstly, the dynamic model is presented. Then a new trajectory tracking algorithm is designed by using the sigma-pi neural network and b...

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Main Authors: Zhiming Chen, Kang Niu, Lei Li
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:International Journal of Aerospace Engineering
Online Access:http://dx.doi.org/10.1155/2019/1510341
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author Zhiming Chen
Kang Niu
Lei Li
author_facet Zhiming Chen
Kang Niu
Lei Li
author_sort Zhiming Chen
collection DOAJ
description In this paper, adaptive tracking control is applied to improve performances of an underactuated quadrotor helicopter with respect to attitude and position control. Firstly, the dynamic model is presented. Then a new trajectory tracking algorithm is designed by using the sigma-pi neural network and backstepping. The paper designs the sigma-pi neural network compensation control law and gives the Lyapunov-type stability analysis. Then the corresponding numerical simulations are performed by using MATLAB. Simulation results are shown to demonstrate the effectiveness of the proposed control strategy, which could reduce tracking error, decrease tracking time, and improve the anti-interference ability of the system.
format Article
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institution Kabale University
issn 1687-5966
1687-5974
language English
publishDate 2019-01-01
publisher Wiley
record_format Article
series International Journal of Aerospace Engineering
spelling doaj-art-88f4807ddf6045b5b3e4925a48a536a32025-02-03T07:26:05ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742019-01-01201910.1155/2019/15103411510341Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural NetworkZhiming Chen0Kang Niu1Lei Li2Micro Satellite Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaShanghai Institute of Space Technology Research Center, Shanghai 201109, ChinaMicro Satellite Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaIn this paper, adaptive tracking control is applied to improve performances of an underactuated quadrotor helicopter with respect to attitude and position control. Firstly, the dynamic model is presented. Then a new trajectory tracking algorithm is designed by using the sigma-pi neural network and backstepping. The paper designs the sigma-pi neural network compensation control law and gives the Lyapunov-type stability analysis. Then the corresponding numerical simulations are performed by using MATLAB. Simulation results are shown to demonstrate the effectiveness of the proposed control strategy, which could reduce tracking error, decrease tracking time, and improve the anti-interference ability of the system.http://dx.doi.org/10.1155/2019/1510341
spellingShingle Zhiming Chen
Kang Niu
Lei Li
Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network
International Journal of Aerospace Engineering
title Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network
title_full Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network
title_fullStr Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network
title_full_unstemmed Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network
title_short Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network
title_sort research on adaptive trajectory tracking algorithm for a quadrotor based on backstepping and the sigma pi neural network
url http://dx.doi.org/10.1155/2019/1510341
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AT kangniu researchonadaptivetrajectorytrackingalgorithmforaquadrotorbasedonbacksteppingandthesigmapineuralnetwork
AT leili researchonadaptivetrajectorytrackingalgorithmforaquadrotorbasedonbacksteppingandthesigmapineuralnetwork