{"title":"System Identification of Flexible Beam Structure Using Artificial Neural Network","authors":"N. A. Jalil, I. Z. Mat Darus","doi":"10.1109/CIMSIM.2013.9","DOIUrl":null,"url":null,"abstract":"This paper presents the development of a nonparametric model that represents the dynamic behaviour of a flexible beam system utilizing several artificial neuralnetwork algorithms. Input-output data used in this study isobtained from Finite Difference algorithm's simulation. Thealgorithm is validated through comparison of its natural frequencies of vibration with the theoretical values. For system identification, non-parametric approach namely ArtificialNeural Network (ANN) is utilized in this study. First is by using Multilayer Perceptron (MLP) and the second method isby using Radial Basis Function (RBF). Several validation testswere carried out to measure the performance of developed model for each technique. Results indicated a superiority for both techniques in modelling a flexible beam structure.","PeriodicalId":249355,"journal":{"name":"2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMSIM.2013.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents the development of a nonparametric model that represents the dynamic behaviour of a flexible beam system utilizing several artificial neuralnetwork algorithms. Input-output data used in this study isobtained from Finite Difference algorithm's simulation. Thealgorithm is validated through comparison of its natural frequencies of vibration with the theoretical values. For system identification, non-parametric approach namely ArtificialNeural Network (ANN) is utilized in this study. First is by using Multilayer Perceptron (MLP) and the second method isby using Radial Basis Function (RBF). Several validation testswere carried out to measure the performance of developed model for each technique. Results indicated a superiority for both techniques in modelling a flexible beam structure.