• DocumentCode
    717292
  • Title

    Hardware implemented adaptive neuro fuzzy system

  • Author

    Brassai, S.T. ; Hajdu, Sz ; Tamas, T. ; Bako, L.

  • Author_Institution
    Dept. of Electr. Eng., Sapientia Hungarian Univ. of Transylvania, Tîrgu Mureş, Romania
  • fYear
    2015
  • fDate
    27-30 May 2015
  • Firstpage
    58
  • Lastpage
    63
  • Abstract
    In the paper the implementation on reconfigurable hardware of a Sugeno type neuro adaptive fuzzy inference system is proposed to be presented. The pipeline and parallel pipeline architecture play an important role in modelling the algorithm for the FPGA based implementation. In order to design the pipeline-parallel model of the controller two different methods were used: high level synthesis tool respectively System Generator. Some of the inference systems sub-modules were implemented in VHDL. The proposed hardware model´s processing speed is very high, allows the controller to be used in real-time applications.
  • Keywords
    control engineering computing; field programmable gate arrays; fuzzy control; fuzzy neural nets; hardware description languages; high level synthesis; neurocontrollers; parallel architectures; pipeline processing; reconfigurable architectures; FPGA based implementation; Sugeno type neuro adaptive fuzzy inference system; VHDL; hardware implemented adaptive neuro fuzzy system; hardware model processing speed; high level synthesis tool; inference systems submodule; parallel pipeline architecture; pipeline-parallel model; reconfigurable hardware; system generator; Fuzzy logic; Generators; Hardware; IP networks; Pipelines; Registers; Synchronization; embedded system; hardware implementation; neuro fuzzy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Carpathian Control Conference (ICCC), 2015 16th International
  • Conference_Location
    Szilvasvarad
  • Print_ISBN
    978-1-4799-7369-9
  • Type

    conf

  • DOI
    10.1109/CarpathianCC.2015.7145046
  • Filename
    7145046