Generation of adjustment strategy of fuzzy-neural force controllers using genetic algorithms with fuzzy evaluation

Kazuo Kiguchi, K. Watanabe, K. Izumi, T. Fukuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an effective force control method in which a fuzzy-neuro force controller is automatically adjusted in accordance with the unknown dynamics of an environment using a neural network. The adjustment strategy of the fuzzy-neural force controller, according to the environment dynamics, is automatically generated by the neural network in off-line manner using genetic algorithms with fuzzy evaluation. The effectiveness of the proposed force controller is evaluated by computer simulation with a 3-DOF planar robot manipulator model.

Original languageEnglish
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
PublisherIEEE Computer Society
Pages620-625
Number of pages6
Volume1
DOIs
Publication statusPublished - 2000
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Kiguchi, K., Watanabe, K., Izumi, K., & Fukuda, T. (2000). Generation of adjustment strategy of fuzzy-neural force controllers using genetic algorithms with fuzzy evaluation. In IECON Proceedings (Industrial Electronics Conference) (Vol. 1, pp. 620-625). [973221] IEEE Computer Society. https://doi.org/10.1109/IECON.2000.973221