{"title":"Using the exhausted particle swarm optimization to design the controller by time-domain objective function","authors":"Huey-Yang Horng","doi":"10.1109/ISNE.2016.7543395","DOIUrl":null,"url":null,"abstract":"A large proportion of industrial systems are represented by LTI transfer functions. The PID controller is one of the most used; the lead-lag controller is a more practical alternative. This paper focused on the design of lead-lag-like controller by optimization of the time-domain objective function. The particle swarm optimization algorithm is selected to finding the optimal solutions. The proposed method force all the particles to search the optimum more exhaustedly. Designers can make a choice in a variety of specifications. If the plant could be modeled as a LTI transfer function, the proposed method will design the controller to be able to approach the required specifications. Computer simulations reveal that the performance can be fully meet or very close to desired.","PeriodicalId":127324,"journal":{"name":"2016 5th International Symposium on Next-Generation Electronics (ISNE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 5th International Symposium on Next-Generation Electronics (ISNE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISNE.2016.7543395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A large proportion of industrial systems are represented by LTI transfer functions. The PID controller is one of the most used; the lead-lag controller is a more practical alternative. This paper focused on the design of lead-lag-like controller by optimization of the time-domain objective function. The particle swarm optimization algorithm is selected to finding the optimal solutions. The proposed method force all the particles to search the optimum more exhaustedly. Designers can make a choice in a variety of specifications. If the plant could be modeled as a LTI transfer function, the proposed method will design the controller to be able to approach the required specifications. Computer simulations reveal that the performance can be fully meet or very close to desired.