• DocumentCode
    624709
  • Title

    Near-optimal control for continuous-time nonlinear systems with control constraints using on-line ADP

  • Author

    Chunbin Qin ; Huaguang Zhang ; Yanhong Luo

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2013
  • fDate
    9-11 June 2013
  • Firstpage
    754
  • Lastpage
    759
  • Abstract
    In this paper, an on-line adaptive dynamic programming (ADP) algorithm is presented to solve the optimal control problem for continuous-time nonlinear systems with control constraints. First, a suitable non-quadratic performance function is introduced to confront control constraints, and then we present an on-line ADP algorithm in which dynamic programming techniques and neural networks are used to solve the optimal control problem for nonlinear systems with control constraints, which is completely different with the traditional ADP algorithm using off-line training, and the corresponding convergence proof is given. Finally, a simulation examples is given to demonstrate the convergence and feasibility of the proposed algorithm.
  • Keywords
    adaptive control; continuous time systems; convergence; dynamic programming; neurocontrollers; nonlinear control systems; optimal control; continuous-time nonlinear system; control constraint; convergence proof; near-optimal control; neural network; nonquadratic performance function; offline training; online ADP algorithm; online adaptive dynamic programming; optimal control problem; Artificial neural networks; Convergence; Equations; Heuristic algorithms; Nonlinear systems; Optimal control; adaptive dynamic programming; control constraint; neural network; nonlinear system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-6248-1
  • Type

    conf

  • DOI
    10.1109/ICICIP.2013.6568173
  • Filename
    6568173