Title :
System Identification of Flexible Beam Structure Using Artificial Neural Network
Author :
Jalil, Nurhanafifi Abd ; Mat Darus, Intan Z.
Author_Institution :
Dept. of Appl. Mech. & Design, Univ. Teknol. Malaysia, Skudai, Malaysia
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.
Keywords :
beams (structures); finite difference methods; flexible structures; mechanical engineering computing; multilayer perceptrons; radial basis function networks; vibrations; ANN; MLP; RBF; artificial neuralnetwork algorithms; dynamic behaviour; finite difference algorithm simulation; flexible beam structure system; input-output data; multilayer perceptron; natural frequency; nonparametric model; radial basis function; system identification; vibration; Artificial neural networks; Delays; Heuristic algorithms; Mathematical model; Neurons; Predictive models; System identification; Finite difference; artificial neural network; multilayer perceptron; radial basis function;
Conference_Titel :
Computational Intelligence, Modelling and Simulation (CIMSim), 2013 Fifth International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4799-2308-3
DOI :
10.1109/CIMSim.2013.9
