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
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-5731-0
DOI :
10.1109/ICSMC.1999.814136
