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Browse Conference Publications > Neural Networks, 1994. IEEE W ... Help

A fuzzy-neural-network-based visual feedback learning control for robot manipulators

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2 Author(s)
Il Hong Suh ; Dept. of Electron. Eng., Hanyang Univ., Kyeongki, South Korea ; Kim, T.W.

A visual feedback learning control algorithm is proposed for a robot manipulator equipped with joint position servos employing fuzzy-membership-function-based neural networks (FMFNN), where weightings of FMFNN's are adjusted in such a way that the robot manipulator with an eye in hand is capable of not only tracking a moving object along the line of sight but also stopping in front of a static object, wherever it is. The training mechanisms of FMFNN are extended to be applied to the control of dynamic systems. To show the validity of the proposed algorithm, several numerical examples are illustrated for a robot manipulator equipped with position servos

Published in:
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:5 )

Date of Conference: 27 Jun-2 Jul 1994

Page(s):
2781 - 2786 vol.5
Meeting Date :
27 Jun 1994-02 Jul 1994
Print ISBN:
0-7803-1901-X
INSPEC Accession Number:
4917361
Conference Location :
Orlando, FL
Digital Object Identifier :
10.1109/ICNN.1994.374671
Product Type:
Conference Publications

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