• DocumentCode
    2765694
  • Title

    Qualitative Adaptive Critics

  • Author

    Shannon, Thaddeus T.

  • Author_Institution
    Portland State Univ., Portland
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    62
  • Lastpage
    67
  • Abstract
    In this paper we compare the use of qualitative adaptive critics to traditional quantitative critics for the design of control systems. Our approach uses a qualitative implementation of the Bellman recursion to train critic and controller networks. This extends previous work with univariate plants to multivariate plants with multiple control objectives. The results indicate that the superior control achieved by more sophisticated model based adaptive critic methods is due to qualitatively more accurate estimates of the gradient of the secondary utility function as opposed to increased numerical precision.
  • Keywords
    adaptive control; control system synthesis; multivariable control systems; adaptive critic methods; control system design; controller networks; multiple control objectives; qualitative adaptive critics; Adaptive control; Computational intelligence; Control systems; Dynamic programming; Feedback; Jacobian matrices; Laboratories; Optimal control; Programmable control; Supervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246660
  • Filename
    1716071