K. Anbumani, DR. R. Ranihemamalini, DR. G. Pechinathan
{"title":"GWO based tuning of PID controller for a heat exchanger process","authors":"K. Anbumani, DR. R. Ranihemamalini, DR. G. Pechinathan","doi":"10.1109/SSPS.2017.8071631","DOIUrl":null,"url":null,"abstract":"In this paper design of controller for a heat exchanger is proposed by using evolutionary algorithm. It is used to find the Grey wolf optimization is one the evolutionary algorithm for better controller tuning. The tuning of PID controller is done by GWO and the simulation are conducted for first order transfer function model of heat exchanger. The performance indices are measured and the measured performance indices are compared with particle swarm optimization technique. From the comparison we realized GWO gave the better optimization for the heat exchanger process.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSPS.2017.8071631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In this paper design of controller for a heat exchanger is proposed by using evolutionary algorithm. It is used to find the Grey wolf optimization is one the evolutionary algorithm for better controller tuning. The tuning of PID controller is done by GWO and the simulation are conducted for first order transfer function model of heat exchanger. The performance indices are measured and the measured performance indices are compared with particle swarm optimization technique. From the comparison we realized GWO gave the better optimization for the heat exchanger process.
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