• DocumentCode
    2345313
  • Title

    The research on the GA-based neuro-predictive control strategy for electric discharge machining process

  • Author

    Zhang, Yun

  • Author_Institution
    Ind. Eng. Inst., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
  • Volume
    2
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    1065
  • Abstract
    In this paper, in accordance with the time-varying and non-linear character in electric discharge machining (EDM) process, a simple single-input single-output system is presented to simulate the EDM process. Based on this, a new type of direct optimizing neuro-predictive control system based on improved genetic algorithms for EDM process is designed. Finally, experimental results show that this system has good self-adaptability and high reliability, which results in the higher productivity.
  • Keywords
    discharges (electric); genetic algorithms; machining; neurocontrollers; nonlinear control systems; predictive control; time-varying systems; electric discharge machining process; genetic algorithm; neuropredictive control; nonlinear systems; time-varying systems; Adaptive control; Algorithm design and analysis; Design optimization; Electrical equipment industry; Genetic algorithms; Machining; Neural networks; Production; Productivity; Time varying systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1382346
  • Filename
    1382346