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

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

doi:10.1109/IECON.2000.973221

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 proceeding › Conference 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 language	English
Title of host publication	IECON Proceedings (Industrial Electronics Conference)
Publisher	IEEE Computer Society
Pages	620-625
Number of pages	6
Volume	1
DOIs	https://doi.org/10.1109/IECON.2000.973221
Publication status	Published - 2000
Externally published	Yes

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Electrical and Electronic Engineering

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10.1109/IECON.2000.973221

Cite this

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title = "Generation of adjustment strategy of fuzzy-neural force controllers using genetic algorithms with fuzzy evaluation",

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.",

author = "Kazuo Kiguchi and K. Watanabe and K. Izumi and T. Fukuda",

year = "2000",

doi = "10.1109/IECON.2000.973221",

language = "English",

volume = "1",

pages = "620--625",

booktitle = "IECON Proceedings (Industrial Electronics Conference)",

publisher = "IEEE Computer Society",

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AU - Kiguchi, Kazuo

AU - Watanabe, K.

AU - Izumi, K.

AU - Fukuda, T.

PY - 2000

Y1 - 2000

N2 - 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.

AB - 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.

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U2 - 10.1109/IECON.2000.973221

DO - 10.1109/IECON.2000.973221

M3 - Conference contribution

AN - SCOPUS:84969246717

VL - 1

SP - 620

EP - 625

BT - IECON Proceedings (Industrial Electronics Conference)

PB - IEEE Computer Society

ER -

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

Abstract

All Science Journal Classification (ASJC) codes

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