• DocumentCode
    423963
  • Title

    Adaptive critic network for prey-predator systems

  • Author

    Calu, Angelica ; Badea-Simionescu, Claudia Lidia

  • Author_Institution
    Inst. of Sci. Comput., Salzburg Univ., Austria
  • Volume
    3
  • fYear
    2004
  • fDate
    25-29 July 2004
  • Firstpage
    1829
  • Abstract
    Calculus of variations provides useful information about the form of the optimal control law for a special class of optimal control problems. Nevertheless, the difficult task still remains to determine the times were the optimal control switches between its admissible boundaries. Using the theoretical results of the Pontryagin´s minimum principle we propose an adaptive critic architecture, which determines the optimal control strategy using approximate dynamic programming and neural networks. The application of the proposed method on a challenging problem of ecology, the optimal control of a prey-predator system, is presented.
  • Keywords
    adaptive control; bang-bang control; dynamic programming; minimum principle; neurocontrollers; predator-prey systems; variational techniques; Pontryagin minimum principle; adaptive critic architecture; adaptive critic network; bang-bang control; dynamic programming; ecology; neural networks; optimal control law; optimal control switches; prey-predator systems; variational calculus; Adaptive control; Adaptive systems; Bang-bang control; Biological system modeling; Calculus; Control systems; Neural networks; Optimal control; Programmable control; Scientific computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-8359-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2004.1380886
  • Filename
    1380886