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Optimized Modeling of Flexible Beam Structure with Pole-Zero Estimation


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DOI: https://doi.org/10.15866/ireme.v13i3.15922

Abstract


In this paper, the optimized mathematical model that represents a flexible beam structure is developed via system identification technique utilizing Artificial Bee Colony (ABC) and Firefly Algorithm (FFA). The flexible beam structure is a common element applied in various fields of engineering and industries. To model the structure, the input and output data are collected experimentally from a well-developed test rig within MATLAB Simulink platform. In order to detect multiple resonance modes, Pseudo Random Binary Sequence (PRBS) signal which contains a wide range of bandwidth frequency is applied as the disturbance force. The best fit of the predicted model is obtained with respect to the minimum value of mean square error (MSE) and the accuracy of the natural frequencies for the significant first and second modes of vibration via pole-zero estimation strategy. Meanwhile, to validate the accuracy of the model compared to the actual system, correlation tests are applied. The comparisons of ABC and FFA performances in system identification are highlighted in this paper. The results reveal that ABC has the superior advantage over FFA in developing an 8th order system which yields minimum MSE of 5.5786×10-12, accurate natural frequencies simultaneously correlates within 95% of the confidence interval.
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Keywords


System Identification; Artificial Bee Colony; Firefly Algorithm; Flexible Beam Structure; Swarm Intelligence

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References


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