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This paper presents a simulated Model Reference Adaptive Controller (MRAC) and its application to regulate steam temperature in distillation process for essential oil extraction system. Steam temperature is one of the most significant parameters that can influence the composition of essential oil yield in terms of quality and quantity. Due to parameter variations and changes in operation conditions...
In this paper, recurrent adaptive neuro-fuzzy inference system (RANFIS) structure has been proposed to solve approximation problem in identifying a global model of steam temperature of packed distillation column in steam distillation essential oil extraction process. The input-output data is acquired from field experimentation via MATLAB Real-time Workshop (RTW) integrated to the plant. The derived...
This paper presents a new method to model a steam temperature in distillation system by using system identification. Three nonlinear models have been compared, i.e. a Hammerstein model, a Wiener model and a Hammerstein-Wiener model. In this work, we propose the utilizing of the piecewise-linear and sigmoid network Hammerstein-Wiener model for single-input single output processes. All the models have...
Controlling a temperature for a distillation system is not an easy task. The lag of this process is normally long. Over heating during the operation can cause quality degradation of the essential oil produced. The conventional method of controlling this kind of process is not capable of giving satisfactory result. In this paper the self tuning PID controller is developed to improvise the steam distillation...
This paper studied the robustness of ARX model by varying the noise sequence adapted to the output of a heating process. The ARX model is fitted from output data which is obtained from a pilot plant of essential oil extraction by applying steam distillation technique. The plant is supplied by 1.5kW power delivered to the heating element which then is converted into PRBS signal as input and produced...
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