4. Results and discussion
4.1. Result from modeling
After measurement and estimating data by the system identification
process, the validation of model are processed by consider
(i) the model order which adjust though number of pole plus zero
which the system need the lowest-order model that adequately
captures the system dynamics, (ii) the best fit which mean the
comparison between output modeling and experimental, the best
fit proportion to the accuracy of model, (iii) FPE and AIC, both of
these values need the lowest for high accuracy of modeling, and
(iv) the nonlinear behaviors by their own characteristics, for example,
linear interval of saturation, zero interval of dead zone, which
we need the simplest function and less complexity to explain the
system. The model properties, estimators, percentage of accuracy,
Final Prediction Error – FPE and Akaikae Information Criterion –
AIC are shown in Table 1.