• DocumentCode
    1925595
  • Title

    Hybrid Modeling and Control of Nonlinear Wet Flue Gas Desulphurization Process

  • Author

    Shi, Yun-tao ; Sun, De-Hui ; Li, Zhi-jun ; Chen, Nian-Si ; Qing, Wang ; Gao, Dong-Jie

  • Author_Institution
    North China Univ. of Technol., Beijing
  • Volume
    2
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    726
  • Lastpage
    730
  • Abstract
    The optimization and control problem of Wet Flue Gas Desulphurization (WFGD) in power plant was studied. Mixed logical dynamical (MLD) model was built to describe hybrid phenomenon of the WFGD process. Based on the mixed logic dynamical model of WFGD, the predictive control optimization problem was solved using the Mixed Integer Quadratic program (MIQP) solver. Therefore the optimal discrete decision variable (the number of LG pump) and the continuous variable decision variable (PH set-point) were obtained on line. The real-time optimization was implemented. A MLD model of PH was also developed based on which the predictive controller of PH was designed. The simulation results indicate that the predictive control based on MLD model scheme presented had good effect.
  • Keywords
    flue gas desulphurisation; nonlinear control systems; predictive control; hybrid modeling; mixed logical dynamical model; nonlinear control; predictive control; wet flue gas desulphurization process; Cybernetics; Flue gases; Logic; Machine learning; Optimal control; Poles and towers; Power generation; Power system modeling; Predictive control; Predictive models; Hybrid systems; Mixed integer quadratic program; Mixed logical dynamics; Predictive control; Wet flue gas desulphurization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370239
  • Filename
    4370239