• DocumentCode
    381037
  • Title

    Neural networks based optimum coagulation dosing rate control applied to water purification system

  • Author

    Bai, Hua ; Gao, Lixin ; Li, Guibai

  • Author_Institution
    Sch. of Mechatronics Eng., Harbin Inst. of Technol., China
  • Volume
    2
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    1432
  • Abstract
    By the analysis of coagulant dosing rate and its influencing factors, the neural network predicting theory was introduced into the water treatment technology creatively and a predicting model of coagulant dosing rate was established. The test results obtained indicate that this model is adaptive and its self-learning ability is effective. The prediction results´ accuracy can be markedly improved by the neural network´s online self-learning. The online predictive control of coagulant dosing rates can be achieved by using this model, and presents an effective way for the realization of optimal coagulant dosing rates.
  • Keywords
    adaptive control; learning (artificial intelligence); neurocontrollers; predictive control; process control; self-adjusting systems; water treatment; adaptive control; coagulant dosing rate; neural networks; online predictive control; process control; self-learning; water purification system; water treatment; Automatic testing; Automation; Coagulation; Control systems; Electronic mail; Mechatronics; Neural networks; Optimal control; Predictive models; Purification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
  • Print_ISBN
    0-7803-7268-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2002.1020819
  • Filename
    1020819