• 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