Modeling and control of steam distillation in essential oil extraction system using Fuzzy Model Reference Learning Control (FMRLC) / Nurhani Kasuan

Malaysia is one of developing countries endowed with abundant resources of raw materials which have to be exploited especially in terms of technological provision in order to sustain and enhance aromatic plants industries and utilization. The essential oil from plant materials contains fragile aromatic molecules that can easily be destroyed or modified by changes caused during the extraction process. Even a subtle difference in extraction process conditions can have a significant effect on oil quality. Temperature one of important parameters that mostly affect essential oil production. In the conventional steam distillation method, high temperatures and extended heat were exposed to botanical plants that can cause thermal degradation to the extracted oil. In this research, a pilot-scale steam distillation system with temperature monitoring and control module was proposed to maintain process temperature at desired response, to avoid waste of energy usage and inconsistency of oil production quality and quantity due to uncertainties. In this study, the range of controlled steam temperature was set between 80oC to 90oC with time constant of desired reference model at 220 seconds with no overshoot. The model of steam temperature has been derived using auto-regression exogenous (ARX) function. For controller module, a Fuzzy Model Reference Learning Controller (FMRLC) was designed and applied to regulate steam temperature based on desired model reference heating profiles…