• DocumentCode
    3192863
  • Title

    Nonlinear Modelling of Alstom Gasifier Using Wiener Model

  • Author

    Xin, Wang ; Liang, Zhao ; Jianhong, Lu ; Wenguo, Xiang

  • Author_Institution
    Sch. of Energy & Environ., Southeast Univ., Nanjing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    11-12 May 2010
  • Firstpage
    804
  • Lastpage
    808
  • Abstract
    A novel nonlinear modelling approach has been developed and implemented on Alstom gasifier using Wiener model. The linear element of the Wiener model was identified by a combined subspace state space method, which integrated MOESP (Multivariable Output-Error State Space) and N4SID (Numerical algorithms for subspace state space system identification) method in the estimation of system matrices. Then a single layer neural network was chosen as the nonlinearity of the model. The proposed model identification method was used to model Alstom gasifier with strong nonlinearity and multivariable couples. The results compared to a combined linear subspace identification method demonstrate that the nonlinear method proposed in this paper behave better approximation.
  • Keywords
    matrix algebra; multivariable systems; neural nets; nonlinear control systems; state-space methods; stochastic processes; Alstom Gasifier; Wiener model; matrices estimation; multivariable output error state space; neural network; nonlinear modelling; numerical algorithms; subspace identification method; Automation; Couplings; Kernel; Mathematical model; Neural networks; State estimation; State-space methods; Stochastic processes; System identification; Vectors; modelling; neural networks; state space methods; subspace; wiener model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-7279-6
  • Electronic_ISBN
    978-1-4244-7280-2
  • Type

    conf

  • DOI
    10.1109/ICICTA.2010.80
  • Filename
    5522746