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

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

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

9 Citations (Scopus)

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.

Original language	English
Title of host publication	2010 Chinese Control and Decision Conference, CCDC 2010
Pages	2898-2901
Number of pages	4
DOIs	https://doi.org/10.1109/CCDC.2010.5498692
Publication status	Published - 2010
Event	2010 Chinese Control and Decision Conference, CCDC 2010 - Xuzhou, China Duration: 26 May 2010 → 28 May 2010

Publication series

Name	2010 Chinese Control and Decision Conference, CCDC 2010

Conference

Conference	2010 Chinese Control and Decision Conference, CCDC 2010
Country/Territory	China
City	Xuzhou
Period	26/05/10 → 28/05/10

Keywords

CPSO-BPNN
FOG
Temperature compensation

Access to Document

10.1109/CCDC.2010.5498692

Cite this

Zhao, D., Chen, J., Han, Y., Song, C., & Liu, Z. (2010). Temperature compensation of FOG scale factor based on CPSO-BPNN. In 2010 Chinese Control and Decision Conference, CCDC 2010 (pp. 2898-2901). Article 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. in 2010 Chinese Control and Decision Conference, CCDC 2010., 5498692, 2010 Chinese Control and Decision Conference, CCDC 2010, pp. 2898-2901, 2010 Chinese Control and Decision Conference, CCDC 2010, Xuzhou, China, 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

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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

Abstract

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Conference

Keywords

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