• DocumentCode
    990440
  • Title

    Use of Hopfield neural networks in optimal guidance

  • Author

    Steck, James E. ; Balakrishnan, Sivasubramanya N.

  • Author_Institution
    Dept. of Mech. Eng., Wichita State Univ., KS
  • Volume
    30
  • Issue
    1
  • fYear
    1994
  • fDate
    1/1/1994 12:00:00 AM
  • Firstpage
    287
  • Lastpage
    293
  • Abstract
    A Hopfield neural network architecture is developed to solve the optimal control problem for homing missile guidance. A linear quadratic optimal control problem is formulated in the form of an efficient parallel computing device known as a Hopfield neural network. Convergence of the Hopfield network is analyzed from a theoretical perspective, showing that the network, as a dynamical system approaches a unique fixed point which is the solution to the optimal control problem at any instant during the missile pursuit. Several target-intercept scenarios are provided to demonstrate the use of the recurrent feedback neural net formulation
  • Keywords
    Hopfield neural nets; aerospace control; missiles; optimal control; Hopfield neural networks; architecture; dynamical system; homing missile guidance; linear quadratic optimal control; optimal guidance; parallel computing; recurrent feedback neural net; target-intercept scenarios; Acceleration; Accelerometers; Artificial neural networks; Biological neural networks; Computer architecture; Hopfield neural networks; Missiles; Modems; Navigation; Neurofeedback; Optimal control; Parallel processing;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/7.250431
  • Filename
    250431