• DocumentCode
    229712
  • Title

    Modeling analysis of switched reluctance motor with ANFIS and D-FNN

  • Author

    Aide Xu

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Dalian Maritime Univ., Dalian, China
  • fYear
    2014
  • fDate
    22-25 Oct. 2014
  • Firstpage
    697
  • Lastpage
    700
  • Abstract
    This paper gives some research about the modeling of Switched Reluctance Motor(SRM). Adaptive network fuzzy inference system(ANFIS) is first used to model the inductance and the torque of SRM. Then the dynamic fuzzy neural network(D-FNN) is applied to model the inductance and the flux linkage of SRM. Compared these two kinds of modeling methods, it is obvious although the D-FNN method can realize the online study, but it is not as accurate as ANFIS.
  • Keywords
    fuzzy neural nets; fuzzy reasoning; power engineering computing; reluctance motors; ANFIS method; D-FNN method; SRM modeling analysis; adaptive network fuzzy inference system; dynamic fuzzy neural network; flux linkage; inductance modeling; switched reluctance motor; torque modeling; Adaptation models; Inductance; Mathematical model; Switched reluctance motors; Torque;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines and Systems (ICEMS), 2014 17th International Conference on
  • Conference_Location
    Hangzhou
  • Type

    conf

  • DOI
    10.1109/ICEMS.2014.7013558
  • Filename
    7013558
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=229712