Parameter estimation of damped compound Pendulum using differential evolution algorithm

Abstract

In this study, the parameter identification of damped compound pendulum prototype is proposed. Control theory has many techniques to solve this problem: the least squares (LS) method and the autoregressive exogenous (ARX) method. Recently, other techniques based on computational intelligence (evolutionary programming) have been used. Evolutionary computation, which would be a very promising approach, an alternative to this method because it does not require any derivative information, contrary to the ordinary gradient-based methods.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 and differential evolution algorithm. PRBS signal is used to be input signal to regulate the motor speed. Whereas, 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. MSE value for LS is 0.0026 and MSE value for DE is 3.6601x10-5. .Based results obtained, it was found that DE have lower MSE than the LS method.