TY - GEN
T1 - Robust feedback error learning method for controller design of nonlinear systems
AU - Chen, Hongping
AU - Hirasawa, Kotaro
AU - Hu, Jinglu
PY - 2004/12/1
Y1 - 2004/12/1
N2 - This paper presents a new robust controller design method for nonlinear system based on feedback error learning (FEL) method and higher order derivatives of Universal Learning Networks (ULNs). Our idea is to make an inverse model robust to signal noise by adding the sensitivity terms to the standard criterion function. Through feedback error learning, the sensitivity term can be minimized as well as usual criterion functions using the higher order derivatives of ULNs. As a result, it is confirmed by using simulation results that NNC robust against signal noise can be obtained.
AB - This paper presents a new robust controller design method for nonlinear system based on feedback error learning (FEL) method and higher order derivatives of Universal Learning Networks (ULNs). Our idea is to make an inverse model robust to signal noise by adding the sensitivity terms to the standard criterion function. Through feedback error learning, the sensitivity term can be minimized as well as usual criterion functions using the higher order derivatives of ULNs. As a result, it is confirmed by using simulation results that NNC robust against signal noise can be obtained.
UR - http://www.scopus.com/inward/record.url?scp=10844261700&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=10844261700&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2004.1380888
DO - 10.1109/IJCNN.2004.1380888
M3 - Conference contribution
AN - SCOPUS:10844261700
SN - 0780383591
T3 - IEEE International Conference on Neural Networks - Conference Proceedings
SP - 1835
EP - 1840
BT - 2004 IEEE International Joint Conference on Neural Networks - Proceedings
T2 - 2004 IEEE International Joint Conference on Neural Networks - Proceedings
Y2 - 25 July 2004 through 29 July 2004
ER -