Temperature compensation of FOG scale factor based on CPSO-BPNN

Dunhui Zhao; Jiabin Chen; Yongqiang Han; Chunlei Song; Zhide Liu

doi:10.1109/CCDC.2010.5498692

Temperature compensation of FOG scale factor based on CPSO-BPNN

Dunhui Zhao^*, Jiabin Chen, Yongqiang Han, Chunlei Song, Zhide Liu

^*此作品的通讯作者

自动化学院

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

9 引用（Scopus）

摘要

The scale factor of fiber optic gyroscope (FOG) varied with the environment temperature. This nonlinear variation seriously influences the precision of the FOG. In this article, the back propagation neural network (BPNN) based on chaos particle swarm optimization (CPSO) is used to compensate the scale factor error. It is testified by experiment, that CPSO-BPNN algorithm is an ideal method to fit the variation of scale factor with temperature, which can greatly decrease the angular rate error of FOG caused by scale factor error and guarantee the measuring precision of FOG at different temperature.

源语言	英语
主期刊名	2010 Chinese Control and Decision Conference, CCDC 2010
页	2898-2901
页数	4
DOI	https://doi.org/10.1109/CCDC.2010.5498692
出版状态	已出版 - 2010
活动	2010 Chinese Control and Decision Conference, CCDC 2010 - Xuzhou, 中国期限: 26 5月 2010 → 28 5月 2010

出版系列

姓名	2010 Chinese Control and Decision Conference, CCDC 2010

会议

会议	2010 Chinese Control and Decision Conference, CCDC 2010
国家/地区	中国
市	Xuzhou
时期	26/05/10 → 28/05/10

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10.1109/CCDC.2010.5498692

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Zhao, D., Chen, J., Han, Y., Song, C., & Liu, Z. (2010). Temperature compensation of FOG scale factor based on CPSO-BPNN. 在 2010 Chinese Control and Decision Conference, CCDC 2010 (页码 2898-2901). 文章 5498692 (2010 Chinese Control and Decision Conference, CCDC 2010). https://doi.org/10.1109/CCDC.2010.5498692

@inproceedings{a32d6baf70cd47aa8cf9f418b917573b,

title = "Temperature compensation of FOG scale factor based on CPSO-BPNN",

abstract = "The scale factor of fiber optic gyroscope (FOG) varied with the environment temperature. This nonlinear variation seriously influences the precision of the FOG. In this article, the back propagation neural network (BPNN) based on chaos particle swarm optimization (CPSO) is used to compensate the scale factor error. It is testified by experiment, that CPSO-BPNN algorithm is an ideal method to fit the variation of scale factor with temperature, which can greatly decrease the angular rate error of FOG caused by scale factor error and guarantee the measuring precision of FOG at different temperature.",

keywords = "CPSO-BPNN, FOG, Temperature compensation",

author = "Dunhui Zhao and Jiabin Chen and Yongqiang Han and Chunlei Song and Zhide Liu",

year = "2010",

doi = "10.1109/CCDC.2010.5498692",

language = "English",

isbn = "9781424451821",

series = "2010 Chinese Control and Decision Conference, CCDC 2010",

pages = "2898--2901",

booktitle = "2010 Chinese Control and Decision Conference, CCDC 2010",

note = "2010 Chinese Control and Decision Conference, CCDC 2010 ; Conference date: 26-05-2010 Through 28-05-2010",

}

Zhao, D, Chen, J, Han, Y, Song, C & Liu, Z 2010, Temperature compensation of FOG scale factor based on CPSO-BPNN. 在 2010 Chinese Control and Decision Conference, CCDC 2010., 5498692, 2010 Chinese Control and Decision Conference, CCDC 2010, 页码 2898-2901, 2010 Chinese Control and Decision Conference, CCDC 2010, Xuzhou, 中国, 26/05/10. https://doi.org/10.1109/CCDC.2010.5498692

TY - GEN

T1 - Temperature compensation of FOG scale factor based on CPSO-BPNN

AU - Zhao, Dunhui

AU - Chen, Jiabin

AU - Han, Yongqiang

AU - Song, Chunlei

AU - Liu, Zhide

PY - 2010

Y1 - 2010

N2 - The scale factor of fiber optic gyroscope (FOG) varied with the environment temperature. This nonlinear variation seriously influences the precision of the FOG. In this article, the back propagation neural network (BPNN) based on chaos particle swarm optimization (CPSO) is used to compensate the scale factor error. It is testified by experiment, that CPSO-BPNN algorithm is an ideal method to fit the variation of scale factor with temperature, which can greatly decrease the angular rate error of FOG caused by scale factor error and guarantee the measuring precision of FOG at different temperature.

AB - The scale factor of fiber optic gyroscope (FOG) varied with the environment temperature. This nonlinear variation seriously influences the precision of the FOG. In this article, the back propagation neural network (BPNN) based on chaos particle swarm optimization (CPSO) is used to compensate the scale factor error. It is testified by experiment, that CPSO-BPNN algorithm is an ideal method to fit the variation of scale factor with temperature, which can greatly decrease the angular rate error of FOG caused by scale factor error and guarantee the measuring precision of FOG at different temperature.

KW - CPSO-BPNN

KW - FOG

KW - Temperature compensation

UR - http://www.scopus.com/inward/record.url?scp=77955366062&partnerID=8YFLogxK

U2 - 10.1109/CCDC.2010.5498692

DO - 10.1109/CCDC.2010.5498692

M3 - Conference contribution

AN - SCOPUS:77955366062

SN - 9781424451821

T3 - 2010 Chinese Control and Decision Conference, CCDC 2010

SP - 2898

EP - 2901

BT - 2010 Chinese Control and Decision Conference, CCDC 2010

T2 - 2010 Chinese Control and Decision Conference, CCDC 2010

Y2 - 26 May 2010 through 28 May 2010

ER -

Temperature compensation of FOG scale factor based on CPSO-BPNN

摘要

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会议

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其它文件与链接

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