• DocumentCode
    2122442
  • Title

    Module-oriented automatic differentiation in nonlinear control

  • Author

    Li, Jin ; Tan, Yuejin ; Liao, Liangcai

  • Author_Institution
    Dept. of Manage., Nat. Univ. of Defense Technol., Changsha
  • fYear
    0
  • fDate
    0-0 0
  • Lastpage
    5
  • Abstract
    In this paper, a module-oriented automatic differentiation (MAD) approach is presented based on traditional automatic differentiation algorithms. This approach can well exploit the sparsity of the model by partitioning it into a series of sequential modules and choosing the best differentiation algorithm for each module accordingly. Numerical results show that for nonlinear system, module-oriented automatic differentiation can calculate the Lie derivatives and Jacobians efficiently
  • Keywords
    chemical industry; nonlinear control systems; state-space methods; Lie derivatives; module-oriented automatic differentiation; nonlinear control system; sequential modules series; Automatic control; Chemical processes; Control system synthesis; Control systems; Fluidization; Jacobian matrices; Nonlinear systems; Partitioning algorithms; Process control; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Control Applications, 2005. ICIECA 2005. International Conference on
  • Conference_Location
    Quito
  • Print_ISBN
    0-7803-9419-4
  • Type

    conf

  • DOI
    10.1109/ICIECA.2005.1644346
  • Filename
    1644346