• DocumentCode
    2787229
  • Title

    Fuzzy Neural Network Control of the Garbage Incinerator

  • Author

    Yu Xiao-hong ; Yang Zhu-zhong ; Yang Tao

  • Author_Institution
    Sch. of Electron. Inf. Eng., Chengdu Univ., Chengdu, China
  • fYear
    2015
  • fDate
    24-26 April 2015
  • Firstpage
    250
  • Lastpage
    253
  • Abstract
    In order to solve the problem of garbage treatment effectively, a control method is proposed based on Takagi-Sugeno (T-S) fuzzy neural network model after analyzing the characteristics of garbage incinerators system and the main factors affecting combustion. A T-S fuzzy neural network model for garbage incinerators control is established which utilizes BP learning algorithm for data training. Then a simulation research is carried out to verify the feasibility and superiority. Results show that the T-S fuzzy neural network control can well track the input in a relative short time. The contrast analysis with conventional PID control and fuzzy control is done to show a better performance under the fuzzy neural network control. The fuzzy neural network control method can adapt to the complex garbage incineration process, which makes it high application value.
  • Keywords
    backpropagation; fuzzy control; fuzzy neural nets; incineration; refuse disposal; three-term control; BP learning algorithm; PID control; T-S fuzzy neural network control method; T-S fuzzy neural network model; Takagi-Sugeno fuzzy neural network model; contrast analysis; data training; fuzzy control; garbage incinerator control system; garbage treatment; Combustion; Fuzzy control; Fuzzy neural networks; Incineration; Neural networks; Process control; Training; BP algorithm; Garbage Incineration; T-S Fuzzy neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-6849-0
  • Type

    conf

  • DOI
    10.1109/ICISCE.2015.62
  • Filename
    7120602