Modeling and control of steam distillation in essential oil extraction system using fuzzy model reference learning control (FMRLC) / Nurhani Kasuan

Malaysia, like many other developing countries, possesses abundant aromatic plant resources. Thus, the extraction of aromatic plant essential oils offers an economic opportunity. Essential oil is one of a plant's primary metabolites, and this valuable product is in great demand in many industries and for numerous applications such as aromatic and fragrance products [1], food and flavorings [2], cosmetics [3], insect repellents and pesticides [4], medicine, and so forth. Moreover, public awareness of natural products has increased, and essential oils provide an alternative to synthetic chemicals and drugs. The consumer demand for essential oil products greatly depends on oil concentration and purity. Furthermore, for industrial standards, essential oil production must be maximized while maintaining reasonable quality, which can be achieved through the advancement of extraction technology. Hence, many research efforts involving the distillation process, from advanced to conventional schemes, have aimed to establish and improve techniques for enhancing the quality and production volumes of essential oil. Based on common practice, the steam distillation technique is still preferred and applied in many industrial and research areas due to several factors such as system cost, cleanliness, productivity, and operational cost [5], and its reliability for the mass production of essential oil [6, 7]…