DocumentCode :
3225601
Title :
The application of genetic algorithm in model identification
Author :
Changliang, Liu ; Jizhen, Liu ; Yuguang, Niu ; Wanye, Yao
Author_Institution :
North China Electr. Power Univ., Baoding, China
Volume :
3
fYear :
2002
fDate :
28-31 Oct. 2002
Firstpage :
1261
Abstract :
A kind of improved genetic algorithm for identifying transfer function of thermal process in power plant is introduced. In the algorithm, floating-point coding, rank-based selection, elitist reservation and grouping method are used, the premature convergence is restrained, the global and local searching ability is improved. The genetic algorithm-based model identification MATLAB program is designed, the transfer functions of thermal process can be got with it according to the operating data log files. The identification results to topical thermal process is given. It is shown by simulation research that accurate identification results can be got no matter what kind of input signal is used, such as step signal, random operating signal, even if there is a strong noise in the input signal.
Keywords :
genetic algorithms; identification; power plants; power system identification; transfer functions; control system; elitist reservation; genetic algorithm; grouping method; identification; power plant; premature convergence; thermal process; transfer function; Convergence; Genetic algorithms; MATLAB; Mathematical model; Polynomials; Power generation; Power system modeling; Signal processing; Signal processing algorithms; Transfer functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Print_ISBN :
0-7803-7490-8
Type :
conf
DOI :
10.1109/TENCON.2002.1182555
Filename :
1182555
Link To Document :
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