• DocumentCode
    1065552
  • Title

    Genetic Optimization for Pulsed-Power System Configuration

  • Author

    Glover, Steven F. ; White, Forest E. ; Reed, Kim W. ; Harden, Michael J.

  • Author_Institution
    Sandia Nat. Labs., Albuquerque, NM
  • Volume
    37
  • Issue
    2
  • fYear
    2009
  • Firstpage
    339
  • Lastpage
    346
  • Abstract
    Pulsed-power systems traditionally have been designed to provide a pulse that is non programmable or requires hardware modifications to adjust the output waveform shape. Advancements in pulsed-power technologies are enabling system designs that allow for greater flexibility such as programmable current shaping. Material science, which uses current pulse shaping to obtain data for the equation of state analysis, is driving much of this work. The programming of pulsed-power systems through the use of simulations and manual curve fitting techniques can work well for systems that only have a few controllable parameters and are generating waveforms with simple spectral content. Complex systems with many controllable parameters become unmanageable for manual trial and error to be effective. This paper discusses the characterization and modeling of a scaled down programmable current adder directed at investigating technical issues that will be encountered in full-scale drivers. A discussion of the procedure used to optimize the adder current output, using genetic algorithms, is presented. The approach to system programmability presented in this paper will allow for a more simplified user interface and system control, as the requirements for flexibility and complexity in future systems increase.
  • Keywords
    adders; genetic algorithms; pulsed power technology; equation of state analysis; genetic algorithms; genetic optimization; manual curve fitting techniques; output waveform shape; programmable current adder; programmable current shaping; pulsed-power system configuration; system programmability; Current adding; current control; equation of state (EOS); genetic algorithms (GAs); identification; isentropic compression; modeling; programmable control; pulsed power;
  • fLanguage
    English
  • Journal_Title
    Plasma Science, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0093-3813
  • Type

    jour

  • DOI
    10.1109/TPS.2008.925637
  • Filename
    4749344