• DocumentCode
    1599663
  • Title

    System identification through neuro-fuzzy methodologies

  • Author

    Cucè, A. ; D´Angelo, G. ; Di Guardo, M. ; Giacalone, B. ; Mazzaglia, S. ; Vinci, C.

  • Author_Institution
    SGS-Thomson Microelectron., Catania, Italy
  • fYear
    1996
  • Firstpage
    129
  • Lastpage
    138
  • Abstract
    The aim of the present work is to propose a way to identify the behaviour of an induction motor supplied by using a DC/AC converter controlled through a pulse width modulation (PWM) technique. Although a mathematical description of the motor is well-known in literature, the model is sensitive to parameters variations. Moreover it is impossible to modelize in a mathematical way the system composed by the motor and the inverter together. A neuro fuzzy network, trained with a set of I/O measures, it is able to identify the whole system. The results proposed show how the behaviour of the identified system matches the real one
  • Keywords
    DC-AC power convertors; PWM invertors; PWM power convertors; fuzzy neural nets; identification; induction motors; DC/AC converter; I/O measures; PWM control; induction motor; inverter; neuro-fuzzy methodologies; pulse width modulation; system identification; Differential equations; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Induction motors; Mathematical model; Neural networks; Pulse width modulation; Pulse width modulation converters; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neuro-Fuzzy Systems, 1996. AT'96., International Symposium on
  • Conference_Location
    Lausanne
  • Print_ISBN
    0-7803-3367-5
  • Type

    conf

  • DOI
    10.1109/ISNFS.1996.603830
  • Filename
    603830