{"title":"Self-scaling laboratory crane fuzzy logic control with anti-swing regulation","authors":"A. Aksjonov, V. Vodovozov, E. Petlenkov","doi":"10.1109/RTUCON.2016.7763088","DOIUrl":null,"url":null,"abstract":"An adaptive fuzzy logic controller for crane positioning along five axes including the self-scaling procedure with an anti-swing regulation is proposed. A fuzzy logic observer with self-tuning universe of discourse is described and experimentally verified on laboratory gantry and tower crane hardware-in-the-loop systems. An anti-swing performance for various load masses is provided. The offered approach guarantees the control precision and reliability and proves to be less dependable on human experts thus eliminating one of the most time-consuming and expensive parts of the crane control system.","PeriodicalId":102691,"journal":{"name":"2016 57th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 57th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON.2016.7763088","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
An adaptive fuzzy logic controller for crane positioning along five axes including the self-scaling procedure with an anti-swing regulation is proposed. A fuzzy logic observer with self-tuning universe of discourse is described and experimentally verified on laboratory gantry and tower crane hardware-in-the-loop systems. An anti-swing performance for various load masses is provided. The offered approach guarantees the control precision and reliability and proves to be less dependable on human experts thus eliminating one of the most time-consuming and expensive parts of the crane control system.