Monitoring and Optimization of Speed Settings for Brushless Direct Current (BLDC) Using Particle Swarm Optimization (PSO)

被引：0
|
作者：
Anshory, Izza [1 ,2 ]
Robandi, Imam [1 ]
Wirawan [1 ]
机构：
[1] Inst Teknol Sepuluh Nopember ITS, Dept Elect Engn, Surabaya 60111, Indonesia
[2] Univ Muhammadiyah Sidoarjo, Dept Elect Engn, Sidoarjo 601271, Indonesia
来源：
2016 IEEE REGION 10 SYMPOSIUM (TENSYMP) | 2016年
关键词：
PID; BLDC motor; PSO algorithm; optimization; MOTOR;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents the setting of the speed of a motor Brushless Direct Current (BLDC) optimized by artificial intelligence. It discusses the comparison between the speed setting of BLDC motor optimized by Particle Swarm Optimization (PSO) and without optimization. The finding shows that the performance of the BLDC motor speed setting optimized by PSO algorithm provides optimal value for the proportional gain constant of 27.0384, integral gain of 5.1108, integral derivatives of 1.9394 and smaller errors of 2,835. In short, the use of PSO algorithm can speed up the stability and reduce the errors.
引用
收藏
页码：243 / 248
页数：6
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