• DocumentCode
    1574132
  • Title

    NN-PLS based on-line component soft-analyzer for Tennessee Eastman process

  • Author

    Hai-qing, Wang ; Gao Yan-chen ; Kai, Song

  • Author_Institution
    Nat. Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China
  • Volume
    4
  • fYear
    2004
  • Firstpage
    3653
  • Abstract
    Filtered by the orthogonal signal correction technique, the selected process measurements projected by NN-PLS algorithm to build the soft component analyzer. Thus a new approach proposed to solve the delayed feedback quality signal of the Tennessee Eastman process by building this soft analyzer. As a result the quality indices can be obtained online in time with enough precision. The simulation results confirm that the soft-analyzer model has satisfying robust and predictive performance and more importantly this soft-analyzer could be as the basis of other advanced process control and on-line monitoring techniques.
  • Keywords
    feedback; least squares approximations; neural nets; signal processing; NN-PLS based on-line component soft-analyzer; Tennessee Eastman process; delayed feedback quality signal; neural-network based partial least squares algorithm; orthogonal signal correction technique; soft component analyzer; Chemical industry; Feeds; Inductors; Industrial control; Monitoring; Predictive models; Process control; Signal analysis; Signal processing; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
  • Print_ISBN
    0-7803-8273-0
  • Type

    conf

  • DOI
    10.1109/WCICA.2004.1343277
  • Filename
    1343277