TY - GEN
T1 - Using accelerated evolutionary programming in self-turning control for uncertainty systems
AU - Wang, Ping
AU - Zhao, Qingjie
AU - Yang, Ruqing
PY - 2006
Y1 - 2006
N2 - This paper proposes a self-turning control scheme based on an artificial neural network (ANN) with accelerated evolutionary programming algorithm. The neural network is used to model the uncertainty process, from which the teacher signals are produced for online regulating the parameters of the controller. The accelerated evolutionary programming is used to train the neural network The experiment results show that the proposed control method can obviously improve the dynamic performance of the system with uncertainty.
AB - This paper proposes a self-turning control scheme based on an artificial neural network (ANN) with accelerated evolutionary programming algorithm. The neural network is used to model the uncertainty process, from which the teacher signals are produced for online regulating the parameters of the controller. The accelerated evolutionary programming is used to train the neural network The experiment results show that the proposed control method can obviously improve the dynamic performance of the system with uncertainty.
KW - ANN
KW - Accelerated evolutionary programming
KW - Self-turning control
UR - http://www.scopus.com/inward/record.url?scp=34547526240&partnerID=8YFLogxK
U2 - 10.1109/ISDA.2006.278
DO - 10.1109/ISDA.2006.278
M3 - Conference contribution
AN - SCOPUS:34547526240
SN - 0769525288
SN - 9780769525280
T3 - Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications
SP - 456
EP - 460
BT - Proceedings - ISDA 2006
T2 - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications
Y2 - 16 October 2006 through 18 October 2006
ER -