• DocumentCode
    2439486
  • Title

    High Precision Prediction of Rolling Load of Finishing Stands by Fuzzy Identification Method

  • Author

    Zhiyong, Wang ; Herong, Jin ; Fucai, Liu

  • Author_Institution
    Coll. of Mech. Eng., Yanshan Univ., Qinhuangdao, China
  • Volume
    2
  • fYear
    2009
  • fDate
    26-27 Aug. 2009
  • Firstpage
    176
  • Lastpage
    179
  • Abstract
    Aimed at the relatively large error of traditional models of rolling load, a new Rolling Load Prediction of Finishing Stands method is set up by Fuzzy Identification. It is based on T-S fuzzy model using triangle-shaped membership functions to calculate the grade of membership for each given pattern, and using Kalman filtering to identify the consequent parameters of fuzzy model. So the prediction precision of rolling load is improved. On the basis of the measured data of the 1580 mm hot strip mill, the relation between the main hot strip mill parameters and rolling load is established using fuzzy model. Experimental results show that the prediction precision is higher, its relative error can be controlled within plusmn4%.
  • Keywords
    Kalman filters; fuzzy control; fuzzy reasoning; fuzzy set theory; hot rolling; intelligent control; parameter estimation; rolling mills; strips; Kalman filtering; T-S fuzzy identification method; finishing stands method; hot strip mill; rolling load prediction; triangle-shaped membership function; Finishing; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Mathematical model; Milling machines; Neural networks; Predictive models; Strips; fuzzy identification; hot continuous rolling; prediction model; rolling load;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human-Machine Systems and Cybernetics, 2009. IHMSC '09. International Conference on
  • Conference_Location
    Hangzhou, Zhejiang
  • Print_ISBN
    978-0-7695-3752-8
  • Type

    conf

  • DOI
    10.1109/IHMSC.2009.168
  • Filename
    5336015