• DocumentCode
    1648061
  • Title

    An Intelligent Control System for Continual Carbonation Decomposition Process

  • Author

    Zhikun, Hu ; Weihua, Gui ; Chunhua, Yang ; Zuoliang, Zhang ; Xiaoli, Wang

  • Author_Institution
    Central South Univ., Changsha
  • fYear
    2007
  • Firstpage
    582
  • Lastpage
    586
  • Abstract
    In alumina production using the sintering process, it is one of the key processes to produce Al(OH)3 using the method of continual carbonation decomposition of sodium aluminate solutions, and the resolution ratio and the last resolution ratio directly affect the output and quality of product. It is such a long time-delay and complex industrial process, which exits much uncertainty and is too complicated to describe with mathematical models, that it can not be controlled properly by traditional methods. In this paper, aimed to control optimal resolution ratio and the last decomposition ratio, the intelligent control system for continual carbonation decomposition process of sodium aluminate solutions is exploited which combined expert control with predictive control strategy. The principle knowledge and experts´ experience of continuous carbonation decomposition process of sodium aluminate solutions is analysed and applied to design a expert control model. And a neural network predicting model is set up to forecast the next output of system which feedback modified the output of expert control model. Thus, the influence of long time-delay was conquered effectively and the process of continual carbonation decomposition was optimal controlled. The practical results show that eligible ratio of decomposition ratio increases by 4%, and average value of decomposition ratio increases by 0.95%. The system is always running well.
  • Keywords
    delays; intelligent control; mathematical analysis; optimal control; predictive control; sintering; alumina production; complex industrial process; continual carbonation decomposition process; intelligent control system; mathematical models; neural network predicting model; optimal control; predictive control strategy; sintering process; time-delay; Control systems; Electrical equipment industry; Industrial control; Intelligent control; Mathematical model; Optimal control; Predictive control; Predictive models; Production; Uncertainty; continual carbonation decomposition; expert control; neural network; predictive control; sodium aluminate solutions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2007. CCC 2007. Chinese
  • Conference_Location
    Hunan
  • Print_ISBN
    978-7-81124-055-9
  • Electronic_ISBN
    978-7-900719-22-5
  • Type

    conf

  • DOI
    10.1109/CHICC.2006.4347204
  • Filename
    4347204