Intelligent Shape Regulation Cooperative Model of Cold Rolling Strip and Its Application

被引:11
|
作者
Yang, Lipo [1 ]
Yu, Huaxin [1 ]
Wang, Dongcheng [1 ]
Zhang, Zhe [1 ]
Jiang, Zhengyi [2 ]
机构
[1] Yanshan Univ, Natl Engn Res Ctr Equipment & Technol Cold Strip, State Key Lab Metastable Mat Sci & Technol, Qinhuangdao 066004, Hebei, Peoples R China
[2] Univ Wollongong, Sch Mech Mat & Mechatron Engn, Wollongong, NSW 2522, Australia
基金
中国国家自然科学基金;
关键词
collaborative regulation; control matrix; effective shape curve; power function; shape closed-loop control; target shape; FLATNESS CONTROL; MATRIX;
D O I
10.1002/srin.201600383
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
A new strip shape control model is established to achieve the synchronizing control of complex shape defects, which can not only takes advantage of the mechanism model's strong analysis ability, but also combines with the fast online calculation function of intelligent model to reduce the poor efficiency regulation. Firstly, the dynamic target strip shape is expressed with the Legendre polynomial contained various components to describe all kinds of online shape targets, so it is easier to compare the shape control effect. Secondly, with the dynamic influence matrix and the efficiency function, some different control methods can be tightly combined in one regulation cycle to carry out the synchronous parallel control and the serial relay regulation, respectively. At the same time, by the DE-ELM method, the intelligent shape control model can play an important role to improve the regulation efficiency of the online strip shape. On the other hand, the collaboration regulation model can make full use of all the effectiveness of each control methods according to their respective characteristics, so that the high precision of the strip shape control is able to be obtained.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] Neural network friction model for cold strip rolling
    Zhao, QL
    Liu, XH
    Wang, GD
    Xu, J
    An, HW
    JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL, 2005, 12 (04) : 35 - 39
  • [42] Neural Network Friction Model for Cold Strip Rolling
    ZHAO Qi-lin1
    2. Baoshon Iron and steel Group Co
    Journal of Iron and Steel Research(International), 2005, (04) : 35 - 39
  • [43] FUZZY APPROACH TO SHAPE CONTROL IN COLD-ROLLING OF STEEL STRIP
    JUNG, JY
    IM, YT
    LEEKWANG, H
    ELECTRONICS LETTERS, 1994, 30 (21) : 1807 - 1808
  • [44] Effect of Cold Rolling Strip Edge Offset on Original Shape Signal
    Yang, Lipo
    Yu, Bingqiang
    MATERIALS PROCESSING AND MANUFACTURING III, PTS 1-4, 2013, 753-755 : 2794 - 2797
  • [45] Reduced order model for shape discrimination of strip rolling
    Sun, Ya-Bo
    Liu, Hong-Min
    Peng, Yan
    Gongcheng Lixue/Engineering Mechanics, 2009, 26 (12): : 204 - 210
  • [46] The application of hot rolled wide strip for the cold rolling industry
    Buddenberg, Heino
    Wilmes, Dirk
    Hellmann, Michael
    STAHL UND EISEN, 2011, 131 (03): : 55 - +
  • [47] Mathematical model for cold rolling and temper rolling process of thin steel strip
    Lee, WH
    KSME INTERNATIONAL JOURNAL, 2002, 16 (10): : 1296 - 1302
  • [48] Mathematical model for cold rolling and temper rolling process of thin steel strip
    Won-Ho Lee
    KSME International Journal, 2002, 16 : 1296 - 1302
  • [49] Analysis of the variation of the cold-rolling characteristics of rolling force, strip shape, stress and temperature, for a three-dimensional strip
    Natl Taiwan Inst of Technology, Taipei, Taiwan
    J Mater Process Technol, 1-4 (326-340):
  • [50] Analysis of the variation of the cold-rolling characteristics of rolling force, strip shape, stress and temperature, for a three-dimensional strip
    Lin, ZC
    Lin, VH
    JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 1995, 54 (1-4) : 326 - 340