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Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network
Joint Authors
Source
International Journal of Aerospace Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-27
Country of Publication
Egypt
No. of Pages
9
Abstract EN
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.
American Psychological Association (APA)
Chen, Zhiming& Niu, Kang& Li, Lei. 2019. Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network. International Journal of Aerospace Engineering،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1156142
Modern Language Association (MLA)
Chen, Zhiming…[et al.]. Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network. International Journal of Aerospace Engineering No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1156142
American Medical Association (AMA)
Chen, Zhiming& Niu, Kang& Li, Lei. Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network. International Journal of Aerospace Engineering. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1156142
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1156142