Abstract: A method is presented for modeling a process using non-steady state values of a process variable implemented in a control unit. The method includes steps of dynamically testing the process and accumulating data points. The data points provide a testing data set including measured values of a response process variable and a manipulated variable. The method includes assigning a first data point within the testing set, computing a dead time value for the testing set, modeling the process over the testing set to determine model-predicted values for the measured response variable, and computing an average error value between each model-predicted values and the measured response variable values. The method further includes centering the model-predicted values over the measured values, computing an optimal fit of the centered model-predicted values, and iteratively repeating these steps until the model-predicted values converge to the measured response variable values.