Assessment of ARMAX structure as a global model for self-refilling steam distillation essential oil extraction system

摘要

In this paper, an essential oil extraction system with self-refilling system is modeled based on input-output data collected from a dedicated acquisition system. The ARMAX model structure is assumed and PRBS signal was used to perturb the process in open-loop manner. Two PRBS signals with different probability band were tested at different operating points. A total of three data sets will be used to evaluate the ARMAX performance as the global model. Since the system is expected to behave in highly-nonlinear manner, it is an interesting experiment to observe the performance of ARMAX which is the linear black box modeling approach in estimating the system dynamic. ARMAX model was estimated by means of prediction error method with LM algorithm. The iteration is fixed to 200 epochs. It is expected that the training data that covers the full operating condition will be the optimum training data. These data are separated into training and testing data by interlacing technique, which make the total number of data 6. For each data, the model order selection is based on ARX structure and MDL information criterion. These data are cross-validated between each others and the validation results are presented and concluded. The performance indexes are the percentages of R{sup}2, adjusted R{sup}2 and NMSE.