Comparison of experimental identification methods using measured data from a turbojet engine

In this work, we compare nine methods of experimental identification (polynomial models, artificial neural networks and deterministic methods). We use measured data from the small turbojet engine iSTC-21v to create experimental models through programming environment MATLAB/Simulink. Comparing the output of these calculated models with the real measured data, we get the amount of the mean absolute error (MAE) and mean absolute percentage error (MAPE) on the basis of which we determine the accuracy of each method.