• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

1993 Fiscal Year Final Research Report Summary

Study on the Lightenning of the Weight of the Underwater Robot Mainpulator

Research Project

Project/Area Number 04302035
Research Category

Grant-in-Aid for Co-operative Research (A)

Allocation TypeSingle-year Grants
Research Field 海洋工学
Research InstitutionKYUSYU UNIVERSITY

Principal Investigator

OGAWARA Yoichi  Kyusyu University, Faculty of Eng., Prof., 工学部, 教授 (20214033)

Co-Investigator(Kenkyū-buntansha) URA Tamaki  TOKYO University, Institute of Industrial Science, Prof., 生研, 教授 (60111564)
YAMATO Hiroyuki  Tokyo University, Faculty of Eng.Assistant Prof., 工学部, 助教授 (50220421)
KOYAMA Takeo  Tokyo University, Faculty of Eng., Prof., 工学部, 教授 (10010696)
KOTERAYAMA Wataru  Kyusyu University, Interdisciplinary Graduate School of Eng. Sciences, Prof., 総理工, 教授 (80038562)
TOYOSADA Masahiro  Kyusyu University, Faculty of Eng., Prof., 工学部, 教授 (30188817)
Project Period (FY) 1992 – 1993
KeywordsWight Lightenning / Position / Force Control / Underwater Robot Manipulator / High Speed Learning / High Trajectory / Learning Feed-Forward Control / Neural Network / Operating Energy Minimization
Research Abstract

1.Study on the force control
(1)We tried to apply the Learning Feed-Forward Controller (LFFC) to the hybrid position and force control system of the underwater robot manipulator. And to hasten the learning speed, we modified the usual learning equation by adding the proportional term. As a result, the system can learn the characteristics of the controlled system with sufficiently high speed for practical use.
(2)By the high speed learning type feed-forward control mode mentioned above, it is considerd to be able to construct the practical control system which is expected to control not only the position of the hand of the manipulator but also the force to the object of operation with very high adaptiveness to the nonlinearity of the manipulator dynamics and to the change of the operating condition.
2.Study on the manipulator hand trajectory which minimizes the energy consumption
(1)It is proved that the operating energy at the inimum consumption can be reduced to about 60% compared with that at the minimum rate of the change of acceleration of the position of the hand.
(2)The trajectory of the inimum operating energy consumption abtained from the solution of the two point boundary value problem can be approximated with neural network with-sufficient accuracy for practical use. And so, it can be expected to construct the trajectory control system under the minimum operating energy consumption.
As a result described above, we could establish the basic technique ;
(〕SY.encircled1.〔) on the force control mode, the technique of avoiding the addition of excess force to the operating object for the lightenning of the manipulator structure,
(〕SY.encircled2.〔) on the minimum operating energy consumption, the technique of the acquistion of the manipuretor hand trajectory for the lightenning of power source of the manipulator.

  • Research Products

    (4 results)

All Other

All Publications (4 results)

  • [Publications] 小川原 陽一: "海洋ロボット用マニピュレータの学習フィードフォワード方式による位置と力の制御" 西部造船会々報. 85号. 101-110 (1993)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 新宅 英司: "海洋ロボット用マニピュレータの操作エネルギー最小化軌道制御に関する研究" 西部造船会々報. 87号. 9 (1994)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] Yoich Ogawara: "Hybrid Position and Force Control of Under Water Manipulator based on Learning Feed-Forward Controller" Transactions of the West-Japan Society of Naval Architects. No.85. 101-110 (1993)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Eiji Shintaku: "Study on a Trajectory Planning of the Under Water Manipulator based on a Minimum Control Energy Criterion" Transactions of the West-Japan Society of Naval Architects. No.87 (anticipation). (1994)

    • Description
      「研究成果報告書概要(欧文)」より

URL: 

Published: 1995-03-27  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi