TY - GEN
T1 - Adaptive control for nonlinear systems based on quasi-ARX neural network
AU - Wang, Lan
AU - Cheng, Yu
AU - Hu, Jinglu
PY - 2009
Y1 - 2009
N2 - When a linear model is used for controlling nonlinear systems solely, it can't satisfy accuracy requirement. Whereas, although a neural network can deal with the accuracy problem, it may lead to instability. In this paper, an adaptive controller is proposed for nonlinear dynamical systems based on linear model and quasi-ARX neural network model. A switching algorithm is designed between the linear and nonlinear models. Theory analysis and simulations are given to show the effectiveness of the proposed method both on stability and accuracy.
AB - When a linear model is used for controlling nonlinear systems solely, it can't satisfy accuracy requirement. Whereas, although a neural network can deal with the accuracy problem, it may lead to instability. In this paper, an adaptive controller is proposed for nonlinear dynamical systems based on linear model and quasi-ARX neural network model. A switching algorithm is designed between the linear and nonlinear models. Theory analysis and simulations are given to show the effectiveness of the proposed method both on stability and accuracy.
UR - http://www.scopus.com/inward/record.url?scp=77949642993&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77949642993&partnerID=8YFLogxK
U2 - 10.1109/NABIC.2009.5393673
DO - 10.1109/NABIC.2009.5393673
M3 - Conference contribution
AN - SCOPUS:77949642993
SN - 9781424456123
T3 - 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings
SP - 1548
EP - 1551
BT - 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings
T2 - 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009
Y2 - 9 December 2009 through 11 December 2009
ER -