Generation of efficient adjustment strategies for a fuzzy-neuro force controller using genetic algorithms - Application to robot force control in an unknown environment

Kazuo Kiguchi, Keigo Watanabe, Toshio Fukuda

研究成果: Contribution to journalArticle査読

14 被引用数 (Scopus)

抄録

This paper presents an effective generation method of adjustment strategies for a fuzzy-neuro force controller (FNFC) of a robot manipulator in an unknown environment. In this method, strategies to adjust the FNFC in accordance with the environment dynamics are automatically generated in off-line manner using genetic algorithms (GA). The generated strategies are stored in a neural network and used for adjusting the FNFC in on-line. Therefore, the FNFC is automatically adjusted in accordance with the unknown dynamics of an environment using the generated strategies which are stored in the neural network. Fuzzy fitness evaluation method is proposed for the effective evolution of the neural network in the GA process. The effectiveness of the generated adjustment strategies of the FNFC has been evaluated by computer simulation with a 3DOF robot manipulator model.

本文言語英語
ページ(範囲)113-126
ページ数14
ジャーナルInformation sciences
145
1-2
DOI
出版ステータス出版済み - 8 1 2002
外部発表はい

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

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