• DocumentCode
    1449120
  • Title

    Learning Petri network and its application to nonlinear system control

  • Author

    Hirasawa, Kotaro ; Ohbayashi, Masanao ; Sakai, Singo ; Hu, Jinglu

  • Author_Institution
    Dept. of Electr. & Electron. Syst. Eng., Kyushu Univ., Fukuoka, Japan
  • Volume
    28
  • Issue
    6
  • fYear
    1998
  • fDate
    12/1/1998 12:00:00 AM
  • Firstpage
    781
  • Lastpage
    789
  • Abstract
    According to recent knowledge of brain science it is suggested that there exists functions distribution, which means that specific parts exist in the brain for realizing specific functions. This paper introduces a new brain-like model called Learning Petri Network (LPN) that has the capability of functions distribution and learning. The idea is to use Petri net to realize the functions distribution and to incorporate the learning and representing ability of neural network into the Petri net. The obtained LPN can be used in the same way as a neural network to model and control dynamic systems, while it is distinctive to a neural network in that it has the capability of functions distribution. An application of the LPN to nonlinear crane control systems is discussed. It is shown via numerical simulations that the proposed LPN controller has superior performance to the commonly-used neural network one
  • Keywords
    Petri nets; backpropagation; neural nets; nonlinear control systems; brain science; dynamic systems; functions distribution; learning Petri network; neural network; nonlinear crane control systems; nonlinear system control; numerical simulations; Biological neural networks; Brain modeling; Control system synthesis; Control systems; Cranes; Humans; Nonlinear control systems; Nonlinear systems; Numerical simulation; Power engineering and energy;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4419
  • Type

    jour

  • DOI
    10.1109/3477.735388
  • Filename
    735388