The longitudinal attitude control of UAV based on GPFN neural network

Langhua Liu; Qingbo Geng; Qing Fei; Qiong Hu

doi:10.1049/cp.2012.1423

The longitudinal attitude control of UAV based on GPFN neural network

Langhua Liu, Qingbo Geng, Qing Fei, Qiong Hu

School of Automation

Beijing Institute of Technology

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

3 Citations (Scopus)

Abstract

At present, more and more applications of Unmanned Aerial Vehicles (UAV) makes the control of UAV to be a hot pot in doing research. In the controlling of UAV, traditional PID controller's parameters are not easily chose and antiinterference ability of the control system is poor. Aiming to improve it, the paper designs a GPFN-PID controller based on GPFN neural network. The controller has the functions of online training, self-training and self-adjusting, which makes the control of UAV longitudinal channel more effective. The simulation results show that both the dynamic characteristics and the anti-interference ability of the control system improve a lot.

Original language	English
Title of host publication	International Conference on Automatic Control and Artificial Intelligence, ACAI 2012
Pages	2146-2149
Number of pages	4
Edition	598 CP
DOIs	https://doi.org/10.1049/cp.2012.1423
Publication status	Published - 2012
Event	International Conference on Automatic Control and Artificial Intelligence, ACAI 2012 - Xiamen, China Duration: 3 Mar 2012 → 5 Mar 2012

Publication series

Name	IET Conference Publications
Number	598 CP
Volume	2012

Conference

Conference	International Conference on Automatic Control and Artificial Intelligence, ACAI 2012
Country/Territory	China
City	Xiamen
Period	3/03/12 → 5/03/12

Keywords

Control of UAV
GPFN
Neural Network
PID
Unmanned Aerial Vehicles

Access to Document

10.1049/cp.2012.1423

Cite this

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title = "The longitudinal attitude control of UAV based on GPFN neural network",

abstract = "At present, more and more applications of Unmanned Aerial Vehicles (UAV) makes the control of UAV to be a hot pot in doing research. In the controlling of UAV, traditional PID controller's parameters are not easily chose and antiinterference ability of the control system is poor. Aiming to improve it, the paper designs a GPFN-PID controller based on GPFN neural network. The controller has the functions of online training, self-training and self-adjusting, which makes the control of UAV longitudinal channel more effective. The simulation results show that both the dynamic characteristics and the anti-interference ability of the control system improve a lot.",

keywords = "Control of UAV, GPFN, Neural Network, PID, Unmanned Aerial Vehicles",

author = "Langhua Liu and Qingbo Geng and Qing Fei and Qiong Hu",

year = "2012",

doi = "10.1049/cp.2012.1423",

language = "English",

isbn = "9781849195379",

series = "IET Conference Publications",

number = "598 CP",

pages = "2146--2149",

booktitle = "International Conference on Automatic Control and Artificial Intelligence, ACAI 2012",

edition = "598 CP",

note = "International Conference on Automatic Control and Artificial Intelligence, ACAI 2012 ; Conference date: 03-03-2012 Through 05-03-2012",

}

Liu, L, Geng, Q, Fei, Q & Hu, Q 2012, The longitudinal attitude control of UAV based on GPFN neural network. in International Conference on Automatic Control and Artificial Intelligence, ACAI 2012. 598 CP edn, IET Conference Publications, no. 598 CP, vol. 2012, pp. 2146-2149, International Conference on Automatic Control and Artificial Intelligence, ACAI 2012, Xiamen, China, 3/03/12. https://doi.org/10.1049/cp.2012.1423

The longitudinal attitude control of UAV based on GPFN neural network. / Liu, Langhua; Geng, Qingbo; Fei, Qing et al.
International Conference on Automatic Control and Artificial Intelligence, ACAI 2012. 598 CP. ed. 2012. p. 2146-2149 (IET Conference Publications; Vol. 2012, No. 598 CP).

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

TY - GEN

T1 - The longitudinal attitude control of UAV based on GPFN neural network

AU - Liu, Langhua

AU - Geng, Qingbo

AU - Fei, Qing

AU - Hu, Qiong

PY - 2012

Y1 - 2012

N2 - At present, more and more applications of Unmanned Aerial Vehicles (UAV) makes the control of UAV to be a hot pot in doing research. In the controlling of UAV, traditional PID controller's parameters are not easily chose and antiinterference ability of the control system is poor. Aiming to improve it, the paper designs a GPFN-PID controller based on GPFN neural network. The controller has the functions of online training, self-training and self-adjusting, which makes the control of UAV longitudinal channel more effective. The simulation results show that both the dynamic characteristics and the anti-interference ability of the control system improve a lot.

AB - At present, more and more applications of Unmanned Aerial Vehicles (UAV) makes the control of UAV to be a hot pot in doing research. In the controlling of UAV, traditional PID controller's parameters are not easily chose and antiinterference ability of the control system is poor. Aiming to improve it, the paper designs a GPFN-PID controller based on GPFN neural network. The controller has the functions of online training, self-training and self-adjusting, which makes the control of UAV longitudinal channel more effective. The simulation results show that both the dynamic characteristics and the anti-interference ability of the control system improve a lot.

KW - Control of UAV

KW - GPFN

KW - Neural Network

KW - PID

KW - Unmanned Aerial Vehicles

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DO - 10.1049/cp.2012.1423

M3 - Conference contribution

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SN - 9781849195379

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SP - 2146

EP - 2149

BT - International Conference on Automatic Control and Artificial Intelligence, ACAI 2012

T2 - International Conference on Automatic Control and Artificial Intelligence, ACAI 2012

Y2 - 3 March 2012 through 5 March 2012

ER -

The longitudinal attitude control of UAV based on GPFN neural network

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Keywords

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