• DocumentCode
    1515815
  • Title

    Neural dynamic optimization for control systems. I. Background

  • Author

    Seong, Chang-Yun ; Widrow, Bernard

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., CA, USA
  • Volume
    31
  • Issue
    4
  • fYear
    2001
  • fDate
    8/1/2001 12:00:00 AM
  • Firstpage
    482
  • Lastpage
    489
  • Abstract
    The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively
  • Keywords
    MIMO systems; computational complexity; dynamic programming; feedback; neural nets; optimal control; optimisation; autonomous vehicles; complexities; control systems; dynamic programming; neural dynamic optimization; nonlinear multi-input-multi-output systems; optimal feedback control; optimal feedback solution; robot arm; Computer networks; Control systems; Dynamic programming; Feedback control; MIMO; Neural networks; Neurofeedback; Optimal control; Optimization methods; Vehicle dynamics;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4419
  • Type

    jour

  • DOI
    10.1109/3477.938254
  • Filename
    938254