LIAO Jun, ZHU Shiqiang, LIN jianya, REN Dexiang. STUDY ON IDENTIFICATION OF FUZZY T-S MODEL BASED ON GENETIC ALGORITHM[J]. INFORMATION AND CONTROL, 1997, 26(2): 141-145,150.
Citation: LIAO Jun, ZHU Shiqiang, LIN jianya, REN Dexiang. STUDY ON IDENTIFICATION OF FUZZY T-S MODEL BASED ON GENETIC ALGORITHM[J]. INFORMATION AND CONTROL, 1997, 26(2): 141-145,150.

STUDY ON IDENTIFICATION OF FUZZY T-S MODEL BASED ON GENETIC ALGORITHM

More Information
  • Received Date: September 01, 1996
  • Published Date: April 19, 1997
  • By using-genetic algorithm, a new approach to identify the fuzzy T-S model that is realized through fuzzy neural network is proposed in this paper. The process of parameter optimization is given in detail. The effectiveness of this approach is testified by a great deal of simulations. Neural network, fuzzy logic and genetic algorithm is fused successfully.
  • 1 廖俊.基于神经网络的模糊控制及其应用研究.浙江大学博士学位论文,1995
    2 Takagi T,M Sugeno.Fuzzy Identification of Systems and it s Application to Modeling and Control.IEEE Trans on SMC,1985,15(1)
    3 Sugeno M,Kang G T.Structure Identification of Fuzzy Model.Fuzzy Sets and Syst,1988,28(1)
    4 Jang J S R.ANFIS Adaptive-net work-based Fuzzy Inference System.IE EE Transon SMC,1993,23(3)
    5 Horikawa S I,et al.On Fuzzy Modeling Using Fuzzy Neural Network with the Back-propagation Algorithm.IEEE Transon NNs,1992,3(5)
    6 张化光.复杂系统的模糊辨识与模糊自适应控制.沈阳:东北大学出版社,1993

Catalog

    Article views (916) PDF downloads (303) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return