Temperature compensation of FOG scale factor based on CPSO-BPNN

Author

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

Author_Institution

Sch. of Autom., Beijing Inst. of Technol., Beijing, China

fYear

2010

fDate

26-28 May 2010

Firstpage

2898

Lastpage

2901

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

backpropagation; computerised instrumentation; error compensation; fibre optic gyroscopes; neural nets; particle swarm optimisation; BPNN; CPSO; FOG; back propagation neural network; chaos particle swarm optimization; environment temperature; error compensation; fiber optic gyroscope; nonlinear variation; scale factor; temperature compensation; Automation; Chaos; Equations; Gyroscopes; Light sources; Optical fiber couplers; Optical fibers; Particle swarm optimization; Temperature distribution; Temperature sensors; CPSO-BPNN; FOG; Temperature Compensation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2010 Chinese

Conference_Location

Xuzhou

Print_ISBN

978-1-4244-5181-4

Electronic_ISBN

978-1-4244-5182-1

Type

conf

DOI

10.1109/CCDC.2010.5498692

Filename

5498692