• DocumentCode
    1672980
  • Title

    Research on hybrid adaptive fuzzy control for the fermentation process

  • Author

    Guan, Shouping ; Zhang, Xin ; Jia, Suna

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2010
  • Firstpage
    3590
  • Lastpage
    3595
  • Abstract
    A multi-variable dynamic model of the glutamic acid fermentation process based on neural network is established. Combining the off-line Optimal control method and the on-line adaptive fuzzy neural network control method, the hybrid fuzzy adaptive fermentation process control model is designed. The off-line optimization track is the main control model, while the adaptive fuzzy neural network based on the genetic algorithm as the assist-control model to modify its output on-line. The simulation results show that application of hybrid fuzzy adaptive controller can effectively overcome all sorts of interference in the fermentation process to ensure a higher rate of acid production.
  • Keywords
    adaptive control; fermentation; fuzzy control; fuzzy neural nets; multivariable control systems; optimal control; fermentation process; genetic algorithm; glutamic acid fermentation; hybrid adaptive fuzzy control; multivariable dynamic model; neural network; optimal control method; optimization track; Adaptation model; Artificial neural networks; Biomass; Fuzzy control; Fuzzy neural networks; Optimization; Process control; fuzzy neural network; genetic algorithm; glutamic acid fermentation; hybrid control model; optimal control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2010 8th World Congress on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-6712-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2010.5553886
  • Filename
    5553886