• DocumentCode
    3471073
  • Title

    The welding power supplies group control system based on T-S model and ANFIS

  • Author

    Zhao, Zhangfeng ; Feng, Jian ; Zhang, Xian ; Wang, Yangyu

  • Author_Institution
    Zhejiang Univ. of Technol., Hangzhou
  • fYear
    2007
  • fDate
    18-21 Aug. 2007
  • Firstpage
    948
  • Lastpage
    952
  • Abstract
    A group control system of welding power supplies with the combination of fuzzy theory and neural networks is proposed in the paper. The membership function of state variables, inference rules in the system, algorithms for fuzzy inference and defuzzification, etc. are analyzed and devised subsequently. Based on those, adaptive neuro-fuzzy inference system (ANFIS) with Tagaki-Sugeno model is achieved. Finally the completed ANFIS is simulated using Simulink toolbox in Matlab, which is used in Membrane-water-wall welding machine for experimentation. The result shows that the design has the advantage of less regulating time (shortened by 22%) and less overshoot (reduced by 40%), and the better dynamic performance is obtained.
  • Keywords
    fuzzy control; fuzzy neural nets; neurocontrollers; power supplies to apparatus; welding; ANFIS; T-S model; Tagaki-Sugeno model; adaptive neuro-fuzzy inference system; defuzzication; fuzzy inference; fuzzy theory; group control; membership function; membrane-water-wall welding machine; neural networks; power supplies; welding; Control system synthesis; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Mathematical model; Neural networks; Power supplies; Power system modeling; Welding; ANFIS; Group control; Simulate; Tagaki-Sugeno model; Welding power supply;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2007 IEEE International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-1531-1
  • Type

    conf

  • DOI
    10.1109/ICAL.2007.4338703
  • Filename
    4338703