%0 Journal Article
%T Neural network predictive control for superheated steam temperature based on modified particle swarm optimization<br>基于改进PSO算法的过热汽温神经网络预测控制
%A XIAO Ben-xian
%A WANG Xiao-wei
%A ZHU Zhi-guo
%A LIU Yi-fu
%A <br>肖本贤
%A 王晓伟
%A 朱志国
%A 刘一福
%J 控制理论与应用
%D 2008
%I 
%X Combining modified particle swarm optimization (MPSO) with neural network predictive control (NNPC), we propose a model-prediction controller,based-on modified particle swarm optimization (MPSO) and radial basis function (RBF) hybrid optimization strategy (MPSO-RBF),and a nonlinear optimization controller,based-on MPSO.For the super- heated steam temperature control,we construct a cascade control system based on the neural network predictive control, and analyze all related problems,including the predictive model,the rolling optimizing algorithm,the feedback adjusting and the simulation-parameter setting.We also present the particle encoded format of MPSO,operating design method,and steps in hybrid optimization algorithm.Simulation experiments of the superheated steam temperature control were done in a super-critical-600 MW direct-current boiler,demonstrating the validity,the superior performance and the application prospects.
%K modified particle swarm optimization(MPSO)
%K RBF neural networks
%K optimized strategy
%K neural network predictive control(NNPC)
%K superheated steam temperature<br>改进PSO算法
%K RBF神经网络
%K 优化策略
%K 神经网络预测控制
%K 过热汽温
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=EFC517161D82F0EB6391D56550E11F40&yid=67289AFF6305E306&vid=C5154311167311FE&iid=38B194292C032A66&sid=1FA4E9C3E6E88FC8&eid=03EE8EDD44A3D4BE&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=9