Neuro Identification for Flexible Cantilever Beam Structure

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In this study, system identification of a flexible beam which undergoes a small deflection due to the disturbance force was conducted. Recursive Least Square (RLS) and several intelligent Neuro identifications were established to acquire the dynamic model of the beam based on One Step-Ahead (OSA) prediction. Comparative assessment between conventional and intelligent methods was investigated in this study with the aim to find the best model that can represents the flexible beam. Neural Network (NN) can be classified according to their structures and learning algorithms. For the purpose of this study, Focused Time-Delay Neural Network (FTDNN), Distributed Time-Delay Neural Network (DTDNN), Nonlinear Autoregressive with Exogeneous Variables (NARX), Elman NN and Radial Basis Function (RBF) were compared their effectiveness in emulating the dynamic behaviour of the system. The performance of the network was observed based on its capability to represents the system with the lowest Mean- Squared-Error (MSE) between the actual and predicted output responses of the models.
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Recursive Least Square; Neural Network; Flexible Cantilever Beam; System Identification

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R. A. Khalil, “Comparison of four neural network learning methods based on genetic algorithm for non- linear dynamic systems identification,” Al-Rafidain Engineering, Vol.20 No.1, Feb. 2012.

Z. B. Nossair, A. A. Madkour, M. A. Awadalla, and M.M. Abdulhady, “System identification using intelligent algorithms”,13th International Conference on Aerospaces Sciences & Aviation Technology, ASAT, May 26-28, 2009.

I. Z. M. Darus, and A. A. M. Al-Khafaji, “Non-parametric modelling of a rectangular flexible plate structure”, Engineering Applications of Artificial Intelligence, 2011.

G. Corsini, M. Diani, R. Grasso,M. D. Martino, P. Mantero, and S. B. Serpico,“Radial Basis Function and Multilayer Perceptron neural networks for sea water optically active parameter estimation in case II waters:a comparison”,INT. J. Remote Sensing, Vol. 24, No. 20, pp. 3917–3932, 2003.

F. M Aldebrez, I. Z. Mat Darus, and M 0. Tokhi, : Dynamic modelling of a twin rotor system in hovering position, International Symposium on Control, Communications and Signal Processing, ISCCSP, pp. 823-826, 2004.

T. Koskela, M. Lehtokangas, J. Saarinen, and K. Kaski, “Time Series Prediction with Multilayer Perceptron, FIR and Elman Neural Networks”.

A. Yazdizadeh, and K. Khorasani, “Adaptive time delay neural network structures for nonlinear system identication”,Neurocomputing 47, pp. 207–240, 2002.

X. Han,W. F. Xie, Z. Fu,and W. D. Luo, “Nonlinear systems identification using dynamic multi-time scale neural networks”,Neurocomputing, 74, pp. 3428–3439, 2011.

B. Liu, H. Li, and T. Wu, “Neural Network identification method applied to the nonlinear system”,Global Congress on Intelligent Systems,Xiamen, China, pp. 120-124. May 2009.

D. T. Pham, and X. Liu, “Identification of linear and nonlinear dynamic systems using recurrent neural networks”,Artificial Intelligence in Engineering 8, pp. 67-75, 1993.

N. A. Jalil, and I. Z. Mat Darus, “Non-parametric Neuro Model of a Flexible Beam Structure,” IEEE Symposium on Computers and Informatics, 2013.

Saad, M.S., Jamaluddin, H., Darus, I.Z.M., Iterative algorithm for active vibration control of flexible beam, (2012) International Review of Mechanical Engineering (IREME), 6 (1), pp. 61-73.

Darus, I.Z.M., Zahidi Rahman, T.A., Mailah, M., Experimental evaluation of active force vibration control of a flexible structure using smart material, (2011) International Review of Mechanical Engineering (IREME), 5 (6), pp. 1088-1094.

A. R. Tavakolpour, I. Z. Mat Darus, M. Mailah, Numerical simulation of a flexible plate system for vibration control, WSEAS Transactions on Systems and Control, 4 (3) , pp. 119-128, 2009

I. Z. Mat Darus, F. M.Aldebrez and M. O.Tokhi, Parametric modelling of a twin rotor system using genetic algorithms, International Symposium on Control, Communications and Signal Processing, ISCCS, pp. 115-118, 2004.

Safizadeh, M.R., Mat Darus, I.Z., Natural frequency analysis of all edges clamped flexible thin plate, (2010) International Review of Mechanical Engineering (IREME), 4 (4), pp. 433-440.


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