{"title":"利用遗传算法和粒子群优化对直流电机 PID 控制器的自动参数检测质量进行调查","authors":"Nhat Quang Dao","doi":"10.46501/ijmtst1004033","DOIUrl":null,"url":null,"abstract":"This article presents the results of a study on selecting optimal PID parameters tuned by Genetic Algorithms (GA) and\nParticle Swarm Optimization (PSO) used for a DC motor. The simulating controller response results show that the PID - GA and\nPID - PSO combination algorithms are superior to traditional methods. The result also allows for the selection of the optimal\nalgorithm - combining the PSO - PID to design a controller that has smaller settling error but larger overshoot and settling time\ncompared to GA-PID method. The simulation was taken in Matlab environments","PeriodicalId":13741,"journal":{"name":"International Journal for Modern Trends in Science and Technology","volume":"70 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Survey on the quality of automatic parameter detection of PID controller for DC motor using Genetic Algorithm and Particle Swarm Optimization\",\"authors\":\"Nhat Quang Dao\",\"doi\":\"10.46501/ijmtst1004033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents the results of a study on selecting optimal PID parameters tuned by Genetic Algorithms (GA) and\\nParticle Swarm Optimization (PSO) used for a DC motor. The simulating controller response results show that the PID - GA and\\nPID - PSO combination algorithms are superior to traditional methods. The result also allows for the selection of the optimal\\nalgorithm - combining the PSO - PID to design a controller that has smaller settling error but larger overshoot and settling time\\ncompared to GA-PID method. The simulation was taken in Matlab environments\",\"PeriodicalId\":13741,\"journal\":{\"name\":\"International Journal for Modern Trends in Science and Technology\",\"volume\":\"70 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal for Modern Trends in Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46501/ijmtst1004033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Modern Trends in Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46501/ijmtst1004033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Survey on the quality of automatic parameter detection of PID controller for DC motor using Genetic Algorithm and Particle Swarm Optimization
This article presents the results of a study on selecting optimal PID parameters tuned by Genetic Algorithms (GA) and
Particle Swarm Optimization (PSO) used for a DC motor. The simulating controller response results show that the PID - GA and
PID - PSO combination algorithms are superior to traditional methods. The result also allows for the selection of the optimal
algorithm - combining the PSO - PID to design a controller that has smaller settling error but larger overshoot and settling time
compared to GA-PID method. The simulation was taken in Matlab environments