• DocumentCode
    2326065
  • Title

    The dynamic fuzzy method to tune the weight factors of neural fuzzy PID controller

  • Author

    Yongquan, Yu ; Ying, Huang ; Bi, Zeng

  • Author_Institution
    Inst. of Intelligent Eng., Guangdong Univ. of Technol., Guangzhou, China
  • Volume
    3
  • fYear
    2004
  • fDate
    25-29 July 2004
  • Firstpage
    2397
  • Abstract
    A new method to modify the weight factors of PID neural network (PIDNN) in neural fuzzy PID controller is presented in this paper. The parameter fuzzy inference base (PFIB) is the structure to carry out the weight-value improving. The principle of PFIB is described and the neural fuzzy PID controller has been used in the steel tube pressure detecting system. The result of running shows that the neural fuzzy PID controller with PFIB has the better and satisfactory behavior for real time industrial control processing.
  • Keywords
    fuzzy control; industrial control; inference mechanisms; neurocontrollers; three-term control; dynamic fuzzy method; neural fuzzy PID controller; parameter fuzzy inference base; real time industrial control processing; steel tube pressure detecting system; weight factors; Automatic control; Bismuth; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Industrial control; Neural networks; Neurons; Three-term control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-8359-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2004.1381003
  • Filename
    1381003