リアルタイム調整関数を用いた無人搬送車ステアリングのニューロ制御 A Steering Control of Automated Guided Vehicles by the Neural Networks Using a Real-Time Tuning Function

この論文にアクセスする

この論文をさがす

著者

抄録

A steering control of automated guided vehicles (AGVs) by neural networks was proposed. It was necessary to adjust the coefficients in the teaching signal according to the degree of learning. Thus, it was desired that they were adjusted automatically, then a steering control strategy of AGVs was proposed with the successive learning neural networks using the auto-tuning function (AT function). Since the change of traveling conditions, for example, a cornering radius and a traveling speed, are not considered, the steering control with the AT function is not practical. In this paper, a steering control strategy of AGVs is proposed with a successive learning neural networks using a real-time tuning function (RT function). The coefficients of the proposed RT function and the initial values of the teaching signal are discussed by the computer simulation. The right and left turnig experiments using the AGV built as a trial are performed and the validity of the RT function is discussed. The excellent traveling control of the AGV is obtained in the case that the traveling conditions are changed. Then the learning of the neural networks is almost terminated and after then the excellent traveling lasts. Thus, the proposed RT function is proved to be very available for the successive learning of neural networks.

収録刊行物

  • 電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society  

    電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society 118(5), 605-610, 1998-05 

    The Institute of Electrical Engineers of Japan

参考文献:  8件

参考文献を見るにはログインが必要です。ユーザIDをお持ちでない方は新規登録してください。

各種コード

  • NII論文ID(NAID)
    10002726708
  • NII書誌ID(NCID)
    AN10012320
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    09136339
  • NDL 記事登録ID
    4474244
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-1608
  • データ提供元
    CJP書誌  NDL  J-STAGE 
ページトップへ