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, 1995Accepted:December 15, 1995Published:August 20, 1996
Keywords:Self-organization, RBF, Neural network, Nonlinear, Learning
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:T. Yamada, N. Yasue, and T. Morimitsu, “Self-Organization and Basis Functions of Neural Network Controllers,” J. Robot. Mechatron., Vol.8 No.4, pp. 333-337, 1996.Data files: