• DocumentCode
    1750657
  • Title

    Interdependent multiobjective control using Biased Neural Network (Biased NN)

  • Author

    Myung, Hwan-chun ; Bien, Z. Zenn

  • Author_Institution
    Dept. of Elec. Eng. & Comp. Sci., Taejon, South Korea
  • Volume
    3
  • fYear
    2001
  • fDate
    25-28 July 2001
  • Firstpage
    1378
  • Abstract
    A Biased Neural Network (Biased-NN) is proposed to solve an interdependent multiobjective control problem. The main idea of the Biased-NN stems from a decoupled fuzzy sliding mode control scheme that provides a simple way to achieve asymptotic stability for a class of decoupled systems. Each neuron in the Biased-NN is used to approximate a sign function in order to replace the sliding mode control structure with the Biased-NN. Such a feature is useful for handling the interdependent multiobjective control problem based upon the proposed supporting strategy. While previous works require a priori knowledge for all the objectives, the proposed method uses only expert knowledge of the objective that is considered the main concern. Simulations are conducted to show the effectiveness of the Biased-NN
  • Keywords
    asymptotic stability; fuzzy control; intelligent control; neurocontrollers; variable structure systems; Biased Neural Network; Biased-NN; a priori knowledge; asymptotic stability; decoupled fuzzy sliding mode control scheme; decoupled systems; expert knowledge; interdependent multiobjective control; interdependent multiobjective control problem; sign function approximation; sliding mode control structure; Asymptotic stability; Cranes; Decision making; Fuzzy control; Fuzzy logic; Fuzzy systems; Neural networks; Neurons; Sliding mode control; Thumb;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-7078-3
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2001.943750
  • Filename
    943750