TY - GEN
T1 - Applying RBF neural network to missile control system parameter optimization
AU - Zhu, Supeng
AU - Fu, Wenxing
AU - Yang, Jun
AU - Luo, Jianjun
PY - 2010
Y1 - 2010
N2 - The PID ( proportional, integral, differential ) control method is widely applied to missile attitude control. The usual empirical method for optimizing the three control parameters of Kp, Ki and Kd can not optimize them on line and in real time. The paper presents the PID parameter optimization method that uses RBF neural network, applies it to a missile's longitudinal control system parameter optimization and verifies its effectiveness through numerical simulation. The simulation results demonstrate preliminarily that the use of RBF neural network can optimize the missile control system parameters on line and in real time.
AB - The PID ( proportional, integral, differential ) control method is widely applied to missile attitude control. The usual empirical method for optimizing the three control parameters of Kp, Ki and Kd can not optimize them on line and in real time. The paper presents the PID parameter optimization method that uses RBF neural network, applies it to a missile's longitudinal control system parameter optimization and verifies its effectiveness through numerical simulation. The simulation results demonstrate preliminarily that the use of RBF neural network can optimize the missile control system parameters on line and in real time.
KW - Missile attitude control
KW - PID (proportional, integral, differential) control
KW - RBF neural network
UR - http://www.scopus.com/inward/record.url?scp=77953072811&partnerID=8YFLogxK
U2 - 10.1109/CAR.2010.5456530
DO - 10.1109/CAR.2010.5456530
M3 - 会议稿件
AN - SCOPUS:77953072811
SN - 9781424451937
T3 - CAR 2010 - 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics
SP - 337
EP - 340
BT - CAR 2010 - 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics
T2 - 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics, CAR 2010
Y2 - 6 March 2010 through 7 March 2010
ER -