• DocumentCode
    2972657
  • Title

    Research on Control Method of Complex Object Based on Human Behavior Data

  • Author

    Zhong Bing-xiang ; Li Tai-fu ; Wang De-biao ; Su Ying-ying

  • Author_Institution
    Coll. of Electron. Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    5486
  • Lastpage
    5489
  • Abstract
    In order to simulate human behavior to achieve intelligent control, in this paper a mathematical modeling method is presented based on Kernel Principal Component Analysis (KPCA) and Support Sector Machine. Sample data from the input space are mapped to high-dimensional feature space by non-linear transformation, then their features are extracted by PCA to decrease dimension of input vector and then the modeling based on support vector regression(SVR) are completed. Through the simulation of skilled people to drive a bike, mathematical model of complex system has reconstructed and intelligent control of complex objects is realized. By simulation and testing on experimental systems, the results are proved that the system model has high precision and good control effect.
  • Keywords
    control system analysis; intelligent control; large-scale systems; principal component analysis; regression analysis; support vector machines; bike; complex object; complex system; control method; high-dimensional feature space; human behavior data; intelligent control; kernel principal component analysis; mathematical modeling; nonlinear transformation; support sector machine; support vector regression; Artificial neural networks; Feature extraction; Fuzzy systems; Kernel; Mathematical model; Principal component analysis; Support vector machines; KPCA; SVR; behavior simulation; complex object; feature extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6880-5
  • Type

    conf

  • DOI
    10.1109/iCECE.2010.1333
  • Filename
    5629507