Neural network based pid control for quadrotor aircraft

Dandan Zhao; Changyin Sun; Qingling Wang; Wankou Yang

doi:10.1007/978-3-319-23862-3_28

Neural network based pid control for quadrotor aircraft

Dandan Zhao
, Changyin Sun
, Qingling Wang
, Wankou Yang

Southeast University, Nanjing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Scopus citations

Abstract

A back propagation neural network (BPNN) based PID control strategy for the attitude of quadrotor is proposed in this paper. Firstly, the architecture and dynamic model of quadrotor are analyzed according to the Newton-Euler Equation. Secondly, a nonlinear attitude model is established on the basis of the mathematical analysis. Thirdly, by eliminating the inverse error adaptively, a BPNN based PID controller is introduced to improve the robustness. Furthermore, PID parameters are adaptively adjusted through the training of neural network weighted coefficients. Finally, numerical examples demonstrate the performance of the designed BPNN based PID controller in terms of precision, adaptability and robustness.

Original language	English
Title of host publication	Intelligence Science and Big Data Engineering
Subtitle of host publication	Big Data and Machine Learning Techniques - 5th International Conference, IScIDE 2015, Revised Selected Papers
Editors	Zhi-Hua Zhou, Baochuan Fu, Fuyuan Hu, Zhancheng Zhang, Zhi-Yong Liu, Yanning Zhang, Xiaofei He, Xinbo Gao
Publisher	Springer Verlag
Pages	287-297
Number of pages	11
ISBN (Print)	9783319238616
DOIs	https://doi.org/10.1007/978-3-319-23862-3_28
State	Published - 2015
Externally published	Yes
Event	5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 - Suzhou, China Duration: 14 Jun 2015 → 16 Jun 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9243
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015
Country/Territory	China
City	Suzhou
Period	14/06/15 → 16/06/15

Keywords

Attitude control
Neural network
PID controller
Quadrotor

Access to Document

10.1007/978-3-319-23862-3_28

Cite this

Zhao, D., Sun, C., Wang, Q., & Yang, W. (2015). Neural network based pid control for quadrotor aircraft. In Z.-H. Zhou, B. Fu, F. Hu, Z. Zhang, Z.-Y. Liu, Y. Zhang, X. He, & X. Gao (Eds.), Intelligence Science and Big Data Engineering: Big Data and Machine Learning Techniques - 5th International Conference, IScIDE 2015, Revised Selected Papers (pp. 287-297). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9243). Springer Verlag. https://doi.org/10.1007/978-3-319-23862-3_28

Zhao, Dandan ; Sun, Changyin ; Wang, Qingling et al. / Neural network based pid control for quadrotor aircraft. Intelligence Science and Big Data Engineering: Big Data and Machine Learning Techniques - 5th International Conference, IScIDE 2015, Revised Selected Papers. editor / Zhi-Hua Zhou ; Baochuan Fu ; Fuyuan Hu ; Zhancheng Zhang ; Zhi-Yong Liu ; Yanning Zhang ; Xiaofei He ; Xinbo Gao. Springer Verlag, 2015. pp. 287-297 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{9bce993e4c2c498e9e4036bf11cc67ef,

title = "Neural network based pid control for quadrotor aircraft",

abstract = "A back propagation neural network (BPNN) based PID control strategy for the attitude of quadrotor is proposed in this paper. Firstly, the architecture and dynamic model of quadrotor are analyzed according to the Newton-Euler Equation. Secondly, a nonlinear attitude model is established on the basis of the mathematical analysis. Thirdly, by eliminating the inverse error adaptively, a BPNN based PID controller is introduced to improve the robustness. Furthermore, PID parameters are adaptively adjusted through the training of neural network weighted coefficients. Finally, numerical examples demonstrate the performance of the designed BPNN based PID controller in terms of precision, adaptability and robustness.",

keywords = "Attitude control, Neural network, PID controller, Quadrotor",

author = "Dandan Zhao and Changyin Sun and Qingling Wang and Wankou Yang",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 ; Conference date: 14-06-2015 Through 16-06-2015",

year = "2015",

doi = "10.1007/978-3-319-23862-3\_28",

language = "英语",

isbn = "9783319238616",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "287--297",

editor = "Zhi-Hua Zhou and Baochuan Fu and Fuyuan Hu and Zhancheng Zhang and Zhi-Yong Liu and Yanning Zhang and Xiaofei He and Xinbo Gao",

booktitle = "Intelligence Science and Big Data Engineering",

}

Zhao, D, Sun, C, Wang, Q & Yang, W 2015, Neural network based pid control for quadrotor aircraft. in Z-H Zhou, B Fu, F Hu, Z Zhang, Z-Y Liu, Y Zhang, X He & X Gao (eds), Intelligence Science and Big Data Engineering: Big Data and Machine Learning Techniques - 5th International Conference, IScIDE 2015, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9243, Springer Verlag, pp. 287-297, 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, Suzhou, China, 14/06/15. https://doi.org/10.1007/978-3-319-23862-3_28

Neural network based pid control for quadrotor aircraft. / Zhao, Dandan; Sun, Changyin; Wang, Qingling et al.
Intelligence Science and Big Data Engineering: Big Data and Machine Learning Techniques - 5th International Conference, IScIDE 2015, Revised Selected Papers. ed. / Zhi-Hua Zhou; Baochuan Fu; Fuyuan Hu; Zhancheng Zhang; Zhi-Yong Liu; Yanning Zhang; Xiaofei He; Xinbo Gao. Springer Verlag, 2015. p. 287-297 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9243).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Neural network based pid control for quadrotor aircraft

AU - Zhao, Dandan

AU - Sun, Changyin

AU - Wang, Qingling

AU - Yang, Wankou

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - A back propagation neural network (BPNN) based PID control strategy for the attitude of quadrotor is proposed in this paper. Firstly, the architecture and dynamic model of quadrotor are analyzed according to the Newton-Euler Equation. Secondly, a nonlinear attitude model is established on the basis of the mathematical analysis. Thirdly, by eliminating the inverse error adaptively, a BPNN based PID controller is introduced to improve the robustness. Furthermore, PID parameters are adaptively adjusted through the training of neural network weighted coefficients. Finally, numerical examples demonstrate the performance of the designed BPNN based PID controller in terms of precision, adaptability and robustness.

AB - A back propagation neural network (BPNN) based PID control strategy for the attitude of quadrotor is proposed in this paper. Firstly, the architecture and dynamic model of quadrotor are analyzed according to the Newton-Euler Equation. Secondly, a nonlinear attitude model is established on the basis of the mathematical analysis. Thirdly, by eliminating the inverse error adaptively, a BPNN based PID controller is introduced to improve the robustness. Furthermore, PID parameters are adaptively adjusted through the training of neural network weighted coefficients. Finally, numerical examples demonstrate the performance of the designed BPNN based PID controller in terms of precision, adaptability and robustness.

KW - Attitude control

KW - Neural network

KW - PID controller

KW - Quadrotor

UR - https://www.scopus.com/pages/publications/84945914742

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DO - 10.1007/978-3-319-23862-3_28

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AN - SCOPUS:84945914742

SN - 9783319238616

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 287

EP - 297

BT - Intelligence Science and Big Data Engineering

A2 - Zhou, Zhi-Hua

A2 - Fu, Baochuan

A2 - Hu, Fuyuan

A2 - Zhang, Zhancheng

A2 - Liu, Zhi-Yong

A2 - Zhang, Yanning

A2 - He, Xiaofei

A2 - Gao, Xinbo

PB - Springer Verlag

T2 - 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015

Y2 - 14 June 2015 through 16 June 2015

ER -

Zhao D, Sun C, Wang Q, Yang W. Neural network based pid control for quadrotor aircraft. In Zhou ZH, Fu B, Hu F, Zhang Z, Liu ZY, Zhang Y, He X, Gao X, editors, Intelligence Science and Big Data Engineering: Big Data and Machine Learning Techniques - 5th International Conference, IScIDE 2015, Revised Selected Papers. Springer Verlag. 2015. p. 287-297. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-23862-3_28

Neural network based pid control for quadrotor aircraft

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