DocumentCode :
2845615
Title :
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
Link To Document :
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