{"title":"Implementation of a simplified modeling scheme for the control of SMA actuators using labview","authors":"E. Chandrasekar, M. Sreekumar","doi":"10.1109/ISMA.2015.7373491","DOIUrl":null,"url":null,"abstract":"The function of Shape Memory Alloy (SMA) actuator is based on the transformation between its low temperature (martensite) and high temperature (austenite) phases. The drawback of SMA actuation is its nonlinear behavior which mainly depends on the heating and cooling methods. Fuzzy Logic Controllers (FLC) are justified as models for many nonlinear functions because of the Universal Approximation Theorem. The objective of this paper is to implement a trained fuzzy logic controller using a simplified modeling scheme for the control of SMA actuators. Since the speed of response of SMA actuation mainly depends on the heating and cooling method, its heat transfer model is presented first. The training algorithm designed based on look-up table scheme is the outcome of heat transfer model of SMA. The fuzzy logic system presented in this work has been simulated in LabVIEW.","PeriodicalId":222454,"journal":{"name":"2015 10th International Symposium on Mechatronics and its Applications (ISMA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 10th International Symposium on Mechatronics and its Applications (ISMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISMA.2015.7373491","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
The function of Shape Memory Alloy (SMA) actuator is based on the transformation between its low temperature (martensite) and high temperature (austenite) phases. The drawback of SMA actuation is its nonlinear behavior which mainly depends on the heating and cooling methods. Fuzzy Logic Controllers (FLC) are justified as models for many nonlinear functions because of the Universal Approximation Theorem. The objective of this paper is to implement a trained fuzzy logic controller using a simplified modeling scheme for the control of SMA actuators. Since the speed of response of SMA actuation mainly depends on the heating and cooling method, its heat transfer model is presented first. The training algorithm designed based on look-up table scheme is the outcome of heat transfer model of SMA. The fuzzy logic system presented in this work has been simulated in LabVIEW.