Neural network predictive control based on particle swarm optimization for urban expressway

被引：0
|
作者：
Lu, Zhilin [1 ,2 ]
Fan, Bingquan [1 ]
Wang, Dongli [2 ]
He, Xiaoyang [2 ]
机构：
[1] Shanghai Univ Sci & Technol, Ctr Res Transports Syst, Shanghai 200093, Peoples R China
[2] Guangxi Univ, Coll Elect Engn, Nanning 530004, Peoples R China
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
关键词：
urban expressway; non-linear predictive control; particle swarm optimization; radial basis function neural network;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A neural network predictive control method based on particle swarm optimization (PSO) for the urban expressway is proposed. A series of serial-parallel structure radial basis function neural networks are used to identify the dynamic traffic flow model of the expressway. A non-linear predictive control algorithm with the constraint conditions is presented, and an on-line optimization algorithm based on PSO is also proposed. The simulation results show that this control algorithm has strong robustness and good control effect. The effectiveness of the on-line optimization based on PSO algorithm is also verified.
引用
收藏
页码：8606 / +
页数：2
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