• DocumentCode
    3465498
  • Title

    Study on synthetic multimode intelligent control for complex industrial process

  • Author

    Wu, Wang

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Xu Chang Univ., Xuchang, China
  • Volume
    1
  • fYear
    2009
  • fDate
    5-6 Dec. 2009
  • Firstpage
    196
  • Lastpage
    199
  • Abstract
    The complex industrial process often with large-scale, time varying behavior, nonlinear, multi-disturbance, and multi-objective, which are hard to create practical mathematical models and the complex plant is difficult to control automatically. A new type of synthetic multimode intelligent control method was proposed by integrating expert control with neural fuzzy network control which called ENFCS was realized in this paper, the structure and principles of ENFCS was analyzed and intelligent harmonized algorithm was programmed, the multi-mode control strategy was proposed and the multi-mode control algorithm programmed, also the NFC was designed and by applied into real complex industrial process plant (THJ-3). The simulation and application indicate the control system is practical and effective.
  • Keywords
    control system analysis; fuzzy control; fuzzy neural nets; intelligent control; large-scale systems; process control; complex industrial process; expert control; fuzzycontrol; intelligent harmonized algorithm; multimode intelligent control; neural network; Algorithm design and analysis; Automatic control; Fuzzy control; Fuzzy neural networks; Industrial control; Intelligent control; Intelligent networks; Intelligent structures; Large-scale systems; Mathematical model; Complex Industrial Process; Expert control; Multi-mode Control; Neural Network Fuzzy control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Test and Measurement, 2009. ICTM '09. International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-4699-5
  • Type

    conf

  • DOI
    10.1109/ICTM.2009.5412964
  • Filename
    5412964