Abstract
This paper proposes comparison of two parameter estimation methods . The first method is standard recursive least squares algorithm. This method uses to estimate system parameters when noise parameters are the same(C=D=1). The second method is data filtering based recursive least squares algorithm. in this method, identification algorithm transform into two sub problems with smaller sizes is used system identification model and noise identification model. Application results show model identification of the data filtering based recursive least squares algorithm. Also, autocorrelation function of measurement residuals is used to validate the model of two methods. Next, system parameters of two methods is estimated and compared. Finally, residual is generated to show the effectiveness and the difference between the two proposed methods using a measurements of the steam drums water level and the water flow to the steam drum.