{"title":"A modified design of PID controller for DC motor drives using Particle Swarm Optimization PSO","authors":"A. El-Gammal, A. A. El-Samahy","doi":"10.1109/POWERENG.2009.4915157","DOIUrl":null,"url":null,"abstract":"This paper presents the application of a new Particle swarm optimization technique for adjusting the gains of a PID speed controller adaptively to give the minimum integral absolute error between the speed demand and the output response, minimum settling time, and minimum overshoot for a separately excited dc drive. The new technique converts all objective functions to a single objective function by deriving a single aggregate objective function using specified or selected weighting factors. Since the optimal PID controller parameters are dependent on the selected weighting factors, the weighting factors was also treated as dynamic optimizing parameters within the Particle Swarm Optimization as a dual optimization and global selection of PID controller optimal parameters as well as best set of weighting factors. Computer simulations and experimental results show that the performance of the optimal PID controller is better than that of the traditional PID controller.","PeriodicalId":246039,"journal":{"name":"2009 International Conference on Power Engineering, Energy and Electrical Drives","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"60","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Power Engineering, Energy and Electrical Drives","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERENG.2009.4915157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 60
Abstract
This paper presents the application of a new Particle swarm optimization technique for adjusting the gains of a PID speed controller adaptively to give the minimum integral absolute error between the speed demand and the output response, minimum settling time, and minimum overshoot for a separately excited dc drive. The new technique converts all objective functions to a single objective function by deriving a single aggregate objective function using specified or selected weighting factors. Since the optimal PID controller parameters are dependent on the selected weighting factors, the weighting factors was also treated as dynamic optimizing parameters within the Particle Swarm Optimization as a dual optimization and global selection of PID controller optimal parameters as well as best set of weighting factors. Computer simulations and experimental results show that the performance of the optimal PID controller is better than that of the traditional PID controller.