• DocumentCode
    2646297
  • Title

    Chaos control in Lorenz systems based on adaptive inverse control of support vector machines

  • Author

    Liu, Ding ; Liu, Han

  • Author_Institution
    Autom. & Inf. Eng. Sch., Xi´´an Univ. of Technol.
  • fYear
    2006
  • fDate
    4-6 Oct. 2006
  • Firstpage
    2024
  • Lastpage
    2029
  • Abstract
    A newly developed chaos control method based on adaptive inverse control of support vector machines (SVM) is proposed which has the excellent nonlinearity approximation ability and better generalization performance. In this control strategy, an identifier is established based on support vector regression and under the invertible condition of control process a controller also designed. It is guaranteed that under the proposed control strategy, uncertain Lorenz system can drive the system state exactly to some specific points. Illustrative examples are used to demonstrate the effectiveness of the proposed design method
  • Keywords
    adaptive control; approximation theory; generalisation (artificial intelligence); nonlinear control systems; regression analysis; support vector machines; uncertain systems; adaptive inverse control; chaos control; generalization; nonlinearity approximation; support vector machines; support vector regression; uncertain Lorenz system; Adaptive control; Adaptive systems; Chaos; Control systems; Optimal control; Programmable control; Risk management; Statistics; Support vector machine classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE
  • Conference_Location
    Munich
  • Print_ISBN
    0-7803-9797-5
  • Electronic_ISBN
    0-7803-9797-5
  • Type

    conf

  • DOI
    10.1109/CACSD-CCA-ISIC.2006.4776951
  • Filename
    4776951