Robot manipulator contact force control application of fuzzy-neural network

Kazuo Kiguchi, Toshio Fukuda

研究成果: Contribution to journalArticle査読

10 被引用数 (Scopus)

抄録

A lot of researches have been done on fuzzy-neural control, the combination of neural networks control which has a learning ability from experiments and fuzzy control which has an ability of dealing with human knowledge, in order to make up for each other's weak points. In this paper, fuzzy-neural controller is introduced for robot manipulator contact force control to an unknown environment. A robot manipulator controller, which approaches, contacts and applies force to the environment, is designed using fuzzy logic in order to realize human like control and then modeled as a neural network to adjust membership functions and rules in order to achieve desired contact force control. Error between desired force and measured force and momentum of robot manipulator are used as input signals of the controller. Simulation has done using a 3DOF planar robot manipulator to confirm the effectiveness of the controller for the tasks of approach, contact and force control.

本文言語英語
ページ(範囲)875-880
ページ数6
ジャーナルUnknown Journal
1
出版ステータス出版済み - 1995
外部発表はい

All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • 制御およびシステム工学

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