An Improved Particle Swarm Optimization Algorithm Based on Fuzzy PID Control

被引：4

作者：

Wang, Zhengsong ^{[1
]}

Wang, Qingkai ^{[2
,3
,4
]}

He, Dakuo ^{[1
]}

Liu, Qing ^{[1
]}

Zhu, Xu ^{[1
]}

Guo, Jiaqing ^{[1
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110004, Liaoning, Peoples R China

[2] Beijing Gen Res Inst Min & Met, Beijing 100160, Peoples R China

[3] Beijing Key Lab Proc Automat Min & Met, Beijing 100160, Peoples R China

[4] State Key Lab Proc Automat Min & Met, Beijing 100160, Peoples R China

来源：

2017 4TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE) | 2017年

基金：

中国国家自然科学基金;

关键词：

Particle swarm optimization; fuzzy PID controller; fuzzy PID-PSO; test functions; traditional PSO; CONVERGENCE;

D O I：

10.1109/ICISCE.2017.178

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Particle swarm optimization (PSO) is a kind of population evolutionary algorithm with profound intelligent background and the research aimed at its evolution feature and evolution law has great theoretical significance. In this paper, the fuzzy PID controller is introduced into PSO algorithm, and then the fuzzy PID-PSO algorithm is presented. Then six commonly used test functions are applied to verify the effectiveness of fuzzy PID-PSO. Besides, several traditional PSO algorithms are applied to test functions, whose simulation results has proved the effectiveness of fuzzy PID-PSO.

引用

页码：835 / 839

页数：5

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