• DocumentCode
    441676
  • Title

    FCMAC based on minesweeping strategy

  • Author

    Hu, Jing-song ; Hu, Gui-wu ; Wang, Jia-bing ; Liu, Bo

  • Author_Institution
    Comput. Sci. & Eng. Dept., South China Univ. of Technol., Guangzhou, China
  • Volume
    2
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    784
  • Abstract
    The fuzzy cerebellar model articulation controller has been widely used to control complex object, but most learning algorithm of CMAC are greedy and local optimization. So the precision is relative low. A fast global strategy, call minesweeping strategy, are presented to improve the global ability of CMAC. The minesweeping strategy lets the current search "jump out", rather than "climb out" step by step, hardly and wanderingly, as simulating annealing and tabu search do, from the current local minimum by exploiting a new area that is far away from all obtained local minima erenow. Therefore the strategy to solve local minimum problem is more successful and faster than other methods. The new method realizes fine control quality to a nonlinear plant, of which mathematic model is not known.
  • Keywords
    fuzzy control; learning (artificial intelligence); search problems; simulated annealing; fuzzy cerebellar model articulation controller; greedy algorithm; learning algorithm; local optimization; minesweeping strategy; nonlinear plant; simulating annealing; tabu search; Brain modeling; Computer science; Educational institutions; Electronic mail; Fuzzy control; Inference algorithms; Mathematical model; Mathematics; Neural networks; Simulated annealing; CMAC; Minesweeping strategy; Nonlinear plant;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527050
  • Filename
    1527050