DocumentCode
420633
Title
Research on neural network predictive control based on particle swarm optimization
Author
Xiao, Jianmei
Author_Institution
Dept. of Electr. & Autom., Shanghai Maritime Univ., China
Volume
1
fYear
2004
fDate
15-19 June 2004
Firstpage
603
Abstract
A new nonlinear predictive control algorithm is presented. The radial basis function neural network is used as multi-step predictive model. The particle swarm optimization algorithm is applied to perform the nonlinear optimization to enhance the convergence and accuracy. The simulation results show that the method is effective.
Keywords
convergence; neurocontrollers; nonlinear control systems; nonlinear programming; predictive control; radial basis function networks; convergence; multistep predictive model; neural network predictive control; nonlinear optimization; nonlinear predictive control algorithm; particle swarm optimization algorithm; radial basis function neural network; Automation; Convergence; Electronic mail; Neural networks; Nonlinear control systems; Particle swarm optimization; Prediction algorithms; Predictive control; Predictive models; Radial basis function networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1340647
Filename
1340647
Link To Document