{"title":"无刷直流电机闭环速度控制的蚱蜢优化算法的实现","authors":"Devendra Potnuru, A. S. Tummala","doi":"10.1504/ijsi.2019.10025730","DOIUrl":null,"url":null,"abstract":"This paper presents a recently proposed grasshopper algorithm for speed control of BLDC motor drive in closed loop. The main objective of this paper is to obtain optimal PID gains of speed controller at different operating conditions. The efficient PID tuning is based on minimisation of integral square error which is the objective function of this optimisation problem. The PID controller is used for speed control of the BLDC motor drive. The drive has been simulated in MATLAB/Simulink environment and is tested at different reference speeds.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"158 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2019-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Implementation of grasshopper optimisation algorithm for closed loop speed control a BLDC motor drive\",\"authors\":\"Devendra Potnuru, A. S. Tummala\",\"doi\":\"10.1504/ijsi.2019.10025730\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a recently proposed grasshopper algorithm for speed control of BLDC motor drive in closed loop. The main objective of this paper is to obtain optimal PID gains of speed controller at different operating conditions. The efficient PID tuning is based on minimisation of integral square error which is the objective function of this optimisation problem. The PID controller is used for speed control of the BLDC motor drive. The drive has been simulated in MATLAB/Simulink environment and is tested at different reference speeds.\",\"PeriodicalId\":44265,\"journal\":{\"name\":\"International Journal of Swarm Intelligence Research\",\"volume\":\"158 1\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2019-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Swarm Intelligence Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijsi.2019.10025730\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Swarm Intelligence Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijsi.2019.10025730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Implementation of grasshopper optimisation algorithm for closed loop speed control a BLDC motor drive
This paper presents a recently proposed grasshopper algorithm for speed control of BLDC motor drive in closed loop. The main objective of this paper is to obtain optimal PID gains of speed controller at different operating conditions. The efficient PID tuning is based on minimisation of integral square error which is the objective function of this optimisation problem. The PID controller is used for speed control of the BLDC motor drive. The drive has been simulated in MATLAB/Simulink environment and is tested at different reference speeds.
期刊介绍:
The mission of the International Journal of Swarm Intelligence Research (IJSIR) is to become a leading international and well-referred journal in swarm intelligence, nature-inspired optimization algorithms, and their applications. This journal publishes original and previously unpublished articles including research papers, survey papers, and application papers, to serve as a platform for facilitating and enhancing the information shared among researchers in swarm intelligence research areas ranging from algorithm developments to real-world applications.