A study of nonlinearity behavior in system dynamic for steam distillation essential oil extraction system

Abstract

This paper presents black box modeling of steam temperature using system identification technique. The steam distillation essential oil extraction system is used to study which level of steam temperature exhibit high nonlinearity characteristic in their dynamic behavior. The model developed based on empirical data perturbed by Random Gaussian Signal (RGS). The linear and nonlinear Auto Regressive with Exogenous input (ARX) models structures are applied and validated using - model fit (%R2), Root Mean Square Error (RMSE) and correlation tests.