Application of Self-Tuning Fuzzy PID (STFPID) Controller on Industrial Essential Oil Extraction System Using System Identification Approach

Abstract

Most of the preferred technique used in the industry for the extraction of essential oil is the steam distillation. The main factors are the system cost, cleanliness, productivity, operational cost and maintenance cost. In extracting the essential oils, few factors have been identified and involved in order to get great quality on the extraction yields. Temperature of extraction is the most significant parameter, which gives impact to the amount of output yield and quality of the oil. The extraction temperature in steam distillation must not be too high to avoid thermal degradation to the oil production. From the previous research, PID controller has been proposed for controller steam temperature in the extraction of essential oil. However, PID controller has some disadvantages in performance during the process to control steam temperature that may reduce the yield and quality of the oil. Therefore, selftuning fuzzy PID controller (STFPID) is proposed to overcome the problem of the PID controller. This research is aimed to propose an application system of STFPID that integrates the induction based on steam distillation system and regulates the steam temperature during the essential oil extraction process. The autoregression exogenous (ARX) structure with the first order model has been done to represent the plant during the controller design. Both STFPID controllers with different shapes of membership functions of the generalized bell and Gaussian performed very well in relation to the settling time, rise time and percentage of overshoot. STFPID controllers with different shapes membership functions of generalized bell performed with 127.3889 seconds in rise time, 162.5660 second in settling time, and 0% of overshoot.