Title :
Adaptive Hopfield neural controller
Author :
Catunda, Sebastian Yuri Cavalcanti ; Cavalcanti, José Homero Feitosa
Author_Institution :
UFPB/CCT/DEE, Campina Grande, PB, Brazil
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;
Conference_Titel :
Industrial Electronics, 1997. ISIE '97., Proceedings of the IEEE International Symposium on
Conference_Location :
Guimaraes
Print_ISBN :
0-7803-3936-3
DOI :
10.1109/ISIE.1997.648913
