{"title":"基于Salp群算法的无刷直流电机位置控制","authors":"O. M. Hussein, N. Yasin","doi":"10.1109/ICOASE56293.2022.10075598","DOIUrl":null,"url":null,"abstract":"The best P and PI controller parameters of the cascade control of the BLDC system are determined using a new artificial intelligence-based optimization method called the slap swarm algorithm (SSA) in this paper. The algorithm's simplicity allows for precise tuning of optimal P and PI controller values. The integral time absolute error (ITAE) was chosen as the fitness function to optimize the controller parameters. Compared with the classical control technique (PID), the SSA approach was found to have good tuning and obtained less rise time, also less (Approximately zero) overshoot, and is more efficient in increasing the step response of the BLDC system, according to the transient response study.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Salp Swarm Algorithm-based Position Control of a BLDC Motor\",\"authors\":\"O. M. Hussein, N. Yasin\",\"doi\":\"10.1109/ICOASE56293.2022.10075598\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The best P and PI controller parameters of the cascade control of the BLDC system are determined using a new artificial intelligence-based optimization method called the slap swarm algorithm (SSA) in this paper. The algorithm's simplicity allows for precise tuning of optimal P and PI controller values. The integral time absolute error (ITAE) was chosen as the fitness function to optimize the controller parameters. Compared with the classical control technique (PID), the SSA approach was found to have good tuning and obtained less rise time, also less (Approximately zero) overshoot, and is more efficient in increasing the step response of the BLDC system, according to the transient response study.\",\"PeriodicalId\":297211,\"journal\":{\"name\":\"2022 4th International Conference on Advanced Science and Engineering (ICOASE)\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 4th International Conference on Advanced Science and Engineering (ICOASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOASE56293.2022.10075598\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOASE56293.2022.10075598","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Salp Swarm Algorithm-based Position Control of a BLDC Motor
The best P and PI controller parameters of the cascade control of the BLDC system are determined using a new artificial intelligence-based optimization method called the slap swarm algorithm (SSA) in this paper. The algorithm's simplicity allows for precise tuning of optimal P and PI controller values. The integral time absolute error (ITAE) was chosen as the fitness function to optimize the controller parameters. Compared with the classical control technique (PID), the SSA approach was found to have good tuning and obtained less rise time, also less (Approximately zero) overshoot, and is more efficient in increasing the step response of the BLDC system, according to the transient response study.