Lutfi Mahardika, A. N. Handayani, H. Herwanto, Kohei Arai
{"title":"Optimization of light tracker movement using fuzzy logic control","authors":"Lutfi Mahardika, A. N. Handayani, H. Herwanto, Kohei Arai","doi":"10.1109/ICOIACT.2018.8350695","DOIUrl":null,"url":null,"abstract":"This paper presents the optimization of light tracker movement using fuzzy logic control. The light tracking system uses dual-axis type that can follow the light in two directions. Dual-axis light tracking system consists of NI myRIO as the microcontroller, four LDRs, and two servo motors. There are three methods that will be compared in this paper, it is non-fuzzy, fuzzy-Mamdani, and fuzzy-Sugeno. The result indicates that fuzzy-Sugeno provides smooth movement better than fuzzy-Mamdani and non-fuzzy methods.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"22 1 1","pages":"384-389"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Information and Communications Technology (ICOIACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOIACT.2018.8350695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents the optimization of light tracker movement using fuzzy logic control. The light tracking system uses dual-axis type that can follow the light in two directions. Dual-axis light tracking system consists of NI myRIO as the microcontroller, four LDRs, and two servo motors. There are three methods that will be compared in this paper, it is non-fuzzy, fuzzy-Mamdani, and fuzzy-Sugeno. The result indicates that fuzzy-Sugeno provides smooth movement better than fuzzy-Mamdani and non-fuzzy methods.
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