{"title":"基于粒子群优化的感应电机最优速度控制技术","authors":"M. Eissa, G. Virk, A. M. Abdelghany, E. S. Ghith","doi":"10.5923/J.IJEE.20130302.04","DOIUrl":null,"url":null,"abstract":"Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. In order to overcome this problem of parameter variation the PI controllers are widely used in industrial plants because it is simple and robust. However there is a problem in tuning PI parameters. So the control engineers are on look for automatic tuning procedures. In recent years, many intelligence algorithms are proposed to tuning the PI parameters. Tuning PI parameters using different optimal algorithms such as the simulated annealing, genetic algorithm, and particle swarm optimization algorithm. In this paper a scheduling PI tuning parameters using particle swarm optimization strategy for an induction motor speed control is proposed. The results of our work have showed a very low transient response and a non-oscillating steady state response with excellent stabilization. The simulation results presented in this paper show the effectiveness of the proposed method, with satisfied response for PSO-PI controller.","PeriodicalId":14041,"journal":{"name":"International journal of energy engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Optimum Induction Motor Speed Control Technique Using Particle Swarm Optimization\",\"authors\":\"M. Eissa, G. Virk, A. M. Abdelghany, E. S. Ghith\",\"doi\":\"10.5923/J.IJEE.20130302.04\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. In order to overcome this problem of parameter variation the PI controllers are widely used in industrial plants because it is simple and robust. However there is a problem in tuning PI parameters. So the control engineers are on look for automatic tuning procedures. In recent years, many intelligence algorithms are proposed to tuning the PI parameters. Tuning PI parameters using different optimal algorithms such as the simulated annealing, genetic algorithm, and particle swarm optimization algorithm. In this paper a scheduling PI tuning parameters using particle swarm optimization strategy for an induction motor speed control is proposed. The results of our work have showed a very low transient response and a non-oscillating steady state response with excellent stabilization. The simulation results presented in this paper show the effectiveness of the proposed method, with satisfied response for PSO-PI controller.\",\"PeriodicalId\":14041,\"journal\":{\"name\":\"International journal of energy engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of energy engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5923/J.IJEE.20130302.04\",\"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 of energy engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5923/J.IJEE.20130302.04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimum Induction Motor Speed Control Technique Using Particle Swarm Optimization
Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. In order to overcome this problem of parameter variation the PI controllers are widely used in industrial plants because it is simple and robust. However there is a problem in tuning PI parameters. So the control engineers are on look for automatic tuning procedures. In recent years, many intelligence algorithms are proposed to tuning the PI parameters. Tuning PI parameters using different optimal algorithms such as the simulated annealing, genetic algorithm, and particle swarm optimization algorithm. In this paper a scheduling PI tuning parameters using particle swarm optimization strategy for an induction motor speed control is proposed. The results of our work have showed a very low transient response and a non-oscillating steady state response with excellent stabilization. The simulation results presented in this paper show the effectiveness of the proposed method, with satisfied response for PSO-PI controller.