DocumentCode
3181343
Title
Adaptive control using combined online and background learning neural network
Author
Johnson, Eric N. ; Oh, Seung-Min
Author_Institution
Sch. of Aerosp. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume
5
fYear
2004
fDate
14-17 Dec. 2004
Firstpage
5433
Abstract
A new adaptive neural network (NN) control concept is proposed with proof of stability properties. The NN learns the plant dynamics with online training, and then combines this with background learning from previously recorded data, which can be advantageous to the NN adaptation convergence characteristics. The network adaptation characteristics of the new combined online and background learning adaptive NN is demonstrated through simulations.
Keywords
adaptive control; convergence; learning (artificial intelligence); neurocontrollers; stability; adaptation convergence characteristics; adaptive neural network control; background learning neural network; online learning neural network; online training; plant dynamics; simulations; stability properties; Adaptive control; Adaptive systems; Aerodynamics; Artificial neural networks; Biological neural networks; Feedforward neural networks; Multi-layer neural network; Neural networks; Programmable control; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2004. CDC. 43rd IEEE Conference on
ISSN
0191-2216
Print_ISBN
0-7803-8682-5
Type
conf
DOI
10.1109/CDC.2004.1429672
Filename
1429672
Link To Document