{"title":"碱燃料电池集成系统动态稳定性改进采用粒子群优化PID控制设计","authors":"Yogita Dwivedi, Vijay Kumar Tayal","doi":"10.1109/RDCAPE.2017.8358322","DOIUrl":null,"url":null,"abstract":"Fuel cell is a well-known green-technology in this modern world. Because of the complex structure of fuel cell, voltage and current control is crucial. In this paper PID control design of alkali fuel cell integrated system in the presence of loading uncertainties is proposed. The PID controller parameters are tuned with the help of particle swarm optimization (PSO) artificial intelligence technique. This improves the integrated system performance subjected to variations in loading conditions. The MATLAB simulation results show the effectiveness of the proposed scheme.","PeriodicalId":442235,"journal":{"name":"2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Dynamic stability improvement of alkali fuel cell integrated system using PSO optimized PID control design\",\"authors\":\"Yogita Dwivedi, Vijay Kumar Tayal\",\"doi\":\"10.1109/RDCAPE.2017.8358322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuel cell is a well-known green-technology in this modern world. Because of the complex structure of fuel cell, voltage and current control is crucial. In this paper PID control design of alkali fuel cell integrated system in the presence of loading uncertainties is proposed. The PID controller parameters are tuned with the help of particle swarm optimization (PSO) artificial intelligence technique. This improves the integrated system performance subjected to variations in loading conditions. The MATLAB simulation results show the effectiveness of the proposed scheme.\",\"PeriodicalId\":442235,\"journal\":{\"name\":\"2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RDCAPE.2017.8358322\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RDCAPE.2017.8358322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic stability improvement of alkali fuel cell integrated system using PSO optimized PID control design
Fuel cell is a well-known green-technology in this modern world. Because of the complex structure of fuel cell, voltage and current control is crucial. In this paper PID control design of alkali fuel cell integrated system in the presence of loading uncertainties is proposed. The PID controller parameters are tuned with the help of particle swarm optimization (PSO) artificial intelligence technique. This improves the integrated system performance subjected to variations in loading conditions. The MATLAB simulation results show the effectiveness of the proposed scheme.
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