• DocumentCode
    2752112
  • Title

    PSO training of the Neural Network application for a controller of the line tracing car

  • Author

    Hoshino, Yukinobu ; Takimoto, Hiroshi

  • Author_Institution
    Dept. of Electron. & Photonic Syst. Eng., Kochi Univ. of Technol., Kami, Japan
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this research, a fuzzy controller system is useful as a key technique to design a machine controller because a fuzzy system can be designed by fuzzy sets, which can be represented using linguistic descriptions of natural language. Those natural languages are able capture human knowledge in fuzzy rules. A fuzzy controller system consists of fuzzy rules and involved techniques. Recently, the research of the fuzzy control has controlled various machines. We verified that fuzzy control can be applicable to a line tracing car control, which is running at a high speed. In our research, designers took a huge amount of time to adjust and setup the fuzzy controller. In order to apply the Neural Network (NN) controller, we designed a simple network system, and setup a PSO_VC and parameters. The PSO_VC (a PSO with Velocity Control) is a speed control strategy for all moving particles on the PSO. In order to configure the NN, a very powerful and quick PSO_VC is used. The PSO_VC is able to adjust all weights and threshold levels. In this paper we present the performances of accurate control and compare results between fuzzy controller and the NN controller.
  • Keywords
    angular velocity control; automobiles; fuzzy control; fuzzy set theory; natural languages; neurocontrollers; particle swarm optimisation; PSO training; PSO-VC; fuzzy controller system; fuzzy rules; fuzzy sets; human knowledge; line tracing car controller; linguistic descriptions; machine controller design; moving particles; natural language; neural network application; simple network system; speed control strategy; threshold levels; Artificial neural networks; DC motors; Fuzzy control; Sensors; Training; Velocity control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4673-1507-4
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2012.6251141
  • Filename
    6251141