DocumentCode
3567580
Title
Control by Online Learning Using a Maximum Sensibility Neural Network
Author
Aguilera-Ruiz, Mario ; Torres-Trevino, Luis M. ; Rodriguez Linan, Juan Angel
Author_Institution
FIME, Univ. Autonoma de Nuevo Leon, San Nicolas de los Garza, Mexico
fYear
2014
Firstpage
118
Lastpage
120
Abstract
In this paper, a maximum sensibility neural network is proposed to make an online learning system of a inverse controller of a plant. This neural network is trained to learn the response of the plant to different random inputs. Once the network is trained, it can be used to control the plant to a desired output.
Keywords
learning systems; neurocontrollers; nonlinear control systems; maximum sensibility neural network; online learning system; plant inverse controller; Biological neural networks; Computational modeling; Control systems; Learning systems; Mathematical model; Neurons; Training; Inverse control; Neural Networks; On line learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence (MICAI), 2014 13th Mexican International Conference on
Print_ISBN
978-1-4673-7010-3
Type
conf
DOI
10.1109/MICAI.2014.24
Filename
7222852
Link To Document