E. Arif, J. Hossen, G. Murthy, Tajrian Mollick, T. Bhuvaneswari, C. Venkataseshaiah
{"title":"Performance Comparisons of Fuzzy Logic and Neuro-Fuzzy Controller Design in Solar Panel Tracking Systems","authors":"E. Arif, J. Hossen, G. Murthy, Tajrian Mollick, T. Bhuvaneswari, C. Venkataseshaiah","doi":"10.1109/SPC.2018.8703980","DOIUrl":null,"url":null,"abstract":"Renewable energy is suitable environmental, energy resources for the new generation. The solar energy system plays a dominant role in electric power generation. The solar panel tracking depends on the sun create the power. The solar panel tracker system among the important element in the PV system, obtaining greatest efficiency several types of the controller has been suggested in the composition to improve the performance. This solar panel tracking process has been used the neuro-fuzzy controller for superior performance. Because in this system neuro-fuzzy controller reduces the sun data error processing and detects the uncertainty weather. Its performance has been studied by using Mat lab simulation. In this system, then compare to \"fuzzy logic controller\" the proposed \"neuro-fuzzy controller\" is found to provide better performance.","PeriodicalId":432464,"journal":{"name":"2018 IEEE Conference on Systems, Process and Control (ICSPC)","volume":"15 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Conference on Systems, Process and Control (ICSPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPC.2018.8703980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Renewable energy is suitable environmental, energy resources for the new generation. The solar energy system plays a dominant role in electric power generation. The solar panel tracking depends on the sun create the power. The solar panel tracker system among the important element in the PV system, obtaining greatest efficiency several types of the controller has been suggested in the composition to improve the performance. This solar panel tracking process has been used the neuro-fuzzy controller for superior performance. Because in this system neuro-fuzzy controller reduces the sun data error processing and detects the uncertainty weather. Its performance has been studied by using Mat lab simulation. In this system, then compare to "fuzzy logic controller" the proposed "neuro-fuzzy controller" is found to provide better performance.