• DocumentCode
    2457134
  • Title

    Understand direct NDP with linear quadratic regulation

  • Author

    Lei Yang ; Si, Jennie ; Tsakalis, K.S.

  • Author_Institution
    Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA
  • fYear
    2004
  • fDate
    2-4 Sept. 2004
  • Firstpage
    374
  • Lastpage
    379
  • Abstract
    This work falls into the general area of approximate dynamic programming. Direct NDP designs are further analyzed using classic control-theoretic sensitivity arguments. The relationship between direct NDP and LQR designs are discussed due to their resemblances in system performance functions. The cart-pole benchmark problem is used to demonstrate the possibility that direct NDP sometimes produces LQR-like designs. It is also shown that given a well-designed direct NDP control system, one can find a corresponding LQR design which exhibits comparable closed-loop performance. The convergence properties are studied by taking direct NDP under the linear LQR control environment.
  • Keywords
    control system synthesis; convergence; dynamic programming; linear quadratic control; neurocontrollers; cart-pole benchmark problem; classic control-theoretic sensitivity arguments; linear quadratic regulation; neural dynamic programming; Approximation methods; Control systems; Convergence; Cost function; Design optimization; Dynamic programming; Equations; Regulators; State estimation; System performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 2004. Proceedings of the 2004 IEEE International Symposium on
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-8635-3
  • Type

    conf

  • DOI
    10.1109/ISIC.2004.1387712
  • Filename
    1387712