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
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;
Conference_Titel :
Decision and Control, 2004. CDC. 43rd IEEE Conference on
Print_ISBN :
0-7803-8682-5
DOI :
10.1109/CDC.2004.1429672
