DocumentCode
1736645
Title
Adaptive Hopfield neural controller
Author
Catunda, Sebastian Yuri Cavalcanti ; Cavalcanti, José Homero Feitosa
Author_Institution
UFPB/CCT/DEE, Campina Grande, PB, Brazil
fYear
1997
Firstpage
1206
Abstract
In this paper, the characteristics of a new neural network controller, composed of two Hopfield neurons, and experimental results obtained from the real time control of a DC motor are described. The model and implementation details of the neuron are shown and the adaptive Hopfield neural controller and its training are described. Also, some experimental results obtained from the positioning of an inverted pendulum using an intelligent control system are shown
Keywords
DC motors; Hopfield neural nets; adaptive control; learning (artificial intelligence); machine control; neurocontrollers; pendulums; position control; real-time systems; DC motor; Hopfield neurons; adaptive Hopfield neural controller; intelligent control system; inverted pendulum positioning; real time control; training; Adaptive control; Circuits; DC motors; Electronic mail; Hopfield neural networks; Intelligent control; Neural networks; Neurons; Programmable control; Switches;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, 1997. ISIE '97., Proceedings of the IEEE International Symposium on
Conference_Location
Guimaraes
Print_ISBN
0-7803-3936-3
Type
conf
DOI
10.1109/ISIE.1997.648913
Filename
648913
Link To Document