Adaptive genetic algorithm for parameter identification of centrifugal compressor

Author

Wang Xiaogang ; Bai Xueliang ; Jiang Bo

Author_Institution

Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China

fYear

2013

fDate

25-27 May 2013

Firstpage

2982

Lastpage

2986

Abstract

Parameters of mechanism model of centrifugal compressor is wide-ranging and artificial selection is difficult to solve. Transforming parameter identification problem of the multistage compressor model into an optimization problem, Adaptive genetic algorithm (AGA) is used to decide the unknown parameters in the model. Model verification results show that the parameters identification can reflect the operating characteristics of centrifugal compressors and the precision of the model is improved.

Keywords

compressors; genetic algorithms; parameter estimation; AGA; adaptive genetic algorithm; artificial selection; centrifugal compressor mechanism model parameter; model verification; multistage compressor model; operating characteristics; optimization problem; parameter identification problem; Adaptation models; Analytical models; Blades; Genetic algorithms; Optimization; Parameter estimation; Temperature measurement; Adaptive Genetic Algorithm; Centrifugal compressor; Mechanism model; Parameter identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2013 25th Chinese

Conference_Location

Guiyang

Print_ISBN

978-1-4673-5533-9

Type

conf

DOI

10.1109/CCDC.2013.6561456

Filename

6561456