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JRM Vol.8 No.4 pp. 333-337
doi: 10.20965/jrm.1996.p0333
(1996)

Paper:

Self-Organization and Basis Functions of Neural Network Controllers

Takayuki Yamada, Norifumi Yasue and Takenori Morimitsu

NTT Access Network Systems Laboratories, Shirane 162, Ooaza Shirakata, Tokaimura, Naka-gun, Ibaragi-Pref., 319-11, Japan

Received:
November 30, 1995
Accepted:
December 15, 1995
Published:
August 20, 1996
Keywords:
Self-organization, RBF, Neural network, Nonlinear, Learning
Abstract

This paper discusses a relationship between a controller for an unknown nonlinear plant and a self-organization capability which changes the structure of the controller. The controllers using both a neural network and a basis function have the potential to realize a nonlinear control system with self-organization capability because they can change their structure through the change of the number of neurons or basis functions.

Cite this article as:
Takayuki Yamada, Norifumi Yasue, and Takenori Morimitsu, “Self-Organization and Basis Functions of Neural Network Controllers,” J. Robot. Mechatron., Vol.8, No.4, pp. 333-337, 1996.
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