Parameter estimation of damped compound Pendulum using Firefly algorithm

Abstract

In this study, the parameter identification of damped compound pendulum prototype is proposed. The procedure used to achieve the parameter identification of the experimental system consisted of input output data collection, ARX model order selection and parameter estimation using conventional method least square (LS) and Firefly algorithm (FA). PRBS signal is used to be input signal to regulate the motor speed. Where, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the ARX model. The performance of the models were validates using statistical analysis based on the mean squares error (MSE) between the actual and predicted output responses of the models. The comparison results between these parameter optimization techniques were highlighted. In this experiment the FA achieves better results than the LS, the firefly algorithm is performed well in terms of mean square error (MSE) with a very low value of 4.3759e-05 while the LS algorithm poor in terms of mean square error (MSE) with value of 0.0026398. The error of model predicted output also show that the FA had the lowest error range that are ±0.015, while the LS range is about ±0.15. All of the results obtained throughout this work show that the FA is a very efficient algorithm.