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

页码：8606 / +

页数：2

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