DocumentCode
349610
Title
A learning algorithm for a neural network in a linearlizer for nonlinear systems
Author
Oki, Toshitaka ; Yamamoto, Toru ; Kaneda, Masahiro ; Shimizu, Akira
Author_Institution
Dept. of Commun. Eng., Okayama Prefectural Univ., Japan
Volume
1
fYear
1999
fDate
1999
Firstpage
466
Abstract
The purpose of this study is to give a design method of a linearlizer by using a neural network (NN) with off-line learning algorithm. This linearlizer works so that the input-output property of the augmented system which consists of the system and the NN may be equivalently equal to that of the linear model. The learning of the NN is performed off-line by using the input and output data of the system. Finally, a numerical simulation is demonstrated to illustrate how to use it in the control problem
Keywords
learning (artificial intelligence); neural nets; nonlinear systems; input-output property; learning algorithm; linearlizer; neural network; nonlinear systems; numerical simulation; Control system synthesis; Delay effects; Design methodology; Intelligent networks; Linear approximation; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location
Tokyo
ISSN
1062-922X
Print_ISBN
0-7803-5731-0
Type
conf
DOI
10.1109/ICSMC.1999.814136
Filename
814136
Link To Document