DocumentCode :
575324
Title :
Discussion of stability of learning type neural network direct controller and its folding behavior
Author :
Yamada, Takayuki
Author_Institution :
Dept. of Comput. & Inf. Sci., Ibaraki Univ., Hitachi, Japan
fYear :
2012
fDate :
20-23 Aug. 2012
Firstpage :
459
Lastpage :
464
Abstract :
This paper discusses stability of a learning type neural network direct controller in the viewpoint of its folding behavior. First, I discuss the stability for the nonlinear plant and the nonlinear neural network. This discussion confirms that we can include the plant Jacobian problem into the tuning problem of the parameter determining the neural network convergence speed because of the folding behavior. Next, I simulate the learning type neural network direct controller using a sine wave as an object plant. This simulation results well match with the result of the stability discussion.
Keywords :
learning systems; neurocontrollers; nonlinear control systems; stability; folding behavior; learning type neural network direct controller; neural network convergence speed; nonlinear neural network; nonlinear plant; object plant; plant Jacobian problem; sine wave; stability; tuning problem; Biological neural networks; Cost function; Equations; Jacobian matrices; Mathematical model; Stability analysis; Adaptive; Controller; Learning; Neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE Annual Conference (SICE), 2012 Proceedings of
Conference_Location :
Akita
ISSN :
pending
Print_ISBN :
978-1-4673-2259-1
Type :
conf
Filename :
6318483
Link To Document :
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