PROCESS CONTROL SYSTEM IDENTIFICATION

System identification is a method for generating workable dynamic response models
based on an observed dataset from an actual system. It is used to give the input-output
relationship of the dynamic response. The objective of this project is to design and
implement System Identification for Liquid System Pilot Plant. The project will also
make comparisons between the conventional and intelligent modeling technique. The
project concentrates on the conventional technique known as empirical modeling and
intelligent modeling by means of System Identification Toolbox. In empirical model
building, models are determines by making small changes in the input variable about
a nominal operating condition. The model developed by using this method provides
the dynamic relationship between selected input and output variables. Matlab
providesthe SystemIdentification Toolboxthat helps to ensure the observedtest data
represents the dynamics of the system under investigation. It provides tools for
creating mathematical models ofdynamic systems based on the observed input-output
data. For the intelligent technique, two model predictors, ARX and ARMAX, are
used to obtain the best model. From the analysis, it shows that the ARX models
exhibit quite the same characteristics as the models obtained from the empirical
technique. By using the System Identification Toolbox, the ARMAX structures are
the best models in representing the actual system. After model validation tests, all
models from both the conventional and intelligent technique are capable of
reproducing observed data with minimum predictive error.