Principle and Application Research of Particle Swarm Optimization

被引：1
|
作者：
Zhang, Zhiqiang [1 ]
Wang, Le [1 ]
Hu, Jiongsong [2 ]
机构：
[1] Guangzhou Univ, Sch Comp Sci & Cyber Engn, Guangzhou, Peoples R China
[2] Univ South China, Sch Comp Sci, Hengyang, Peoples R China
来源：
2020 5TH INTERNATIONAL CONFERENCE ON MECHANICAL, CONTROL AND COMPUTER ENGINEERING (ICMCCE 2020) | 2020年
基金：
中国国家自然科学基金;
关键词：
particle swarm optimization algorithm; principle; chaotic control system; system simulation;
D O I：
10.1109/ICMCCE51767.2020.00359
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
With the increasing size and complexity of modern industrial production, the requirements for control systems are becoming higher and higher. The particle swarm optimization algorithm is a population-based stochastic optimization method. This paper first introduces the origin, principle and implementation steps of PSO algorithm, and then introduces the application of particle swarm algorithm in control system. In this paper, the fuzzy control strategy based on particle swarm optimization is proposed to improve the performance of fuzzy control. The design idea and implementation of the control strategy are described in detail. Finally, the system simulation is carried out with Matlab, and the simulation results are compared and analyzed. The results show that the control strategy can effectively improve the dynamic quality and steady-state accuracy of the control system, and has a good practical application prospect.
引用
收藏
页码：1638 / 1642
页数：5
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