• DocumentCode
    1836742
  • Title

    The Research Survey of System Identification Method

  • Author

    Li Fu ; Pengfei Li

  • Author_Institution
    Autom. Dept., Shenyang Aerosp. Univ., Shenyang, China
  • Volume
    2
  • fYear
    2013
  • fDate
    26-27 Aug. 2013
  • Firstpage
    397
  • Lastpage
    401
  • Abstract
    At present, as a method of establishing mathematical model of the system, the system identification has been widely applied to the automatic control, aviation, space flight, astronomy, medicine, biology, marine ecology and society, economics and many other fields. With the rapid development of science and technology, the status of system identification technique in various disciplines is becoming increasingly important. This paper firstly introduces traditional methods of linear system identification, and then modern methods of nonlinear system identification are introduced briefly Based on the neural network, fuzzy logic, genetic algorithm, swarm intelligence optimization algorithms, auxiliary model identification algorithm, multi-innovation identification algorithm and hierarchical identification algorithm, and finally the author analyses the developing tendency and prospect of system identification.
  • Keywords
    fuzzy logic; genetic algorithms; identification; linear systems; neural nets; nonlinear systems; swarm intelligence; auxiliary model identification algorithm; fuzzy logic; genetic algorithm; hierarchical identification algorithm; linear system identification; mathematical model; multiinnovation identification algorithm; neural network; nonlinear system identification; swarm intelligence optimization algorithms; system identification method; Algorithm design and analysis; Genetic algorithms; Mathematical model; Neural networks; Nonlinear systems; Optimization; System identification; System identification; auxiliary model identification algorithm; fuzzy logic; genetic algorithm; hierarchical identification algorithm; multi-innovation identification algorithm; neural network; swarm intelligence optimization algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-0-7695-5011-4
  • Type

    conf

  • DOI
    10.1109/IHMSC.2013.242
  • Filename
    6642770