NDLI: Model Predictive Control for steam distillation essential oil extraction process

Content Provider	IEEE Xplore Digital Library
Author	Tajjudin, N. Rahiman, M.H.F. Taib, M.N.
Copyright Year	2009
Description	Author affiliation: Faculty of Electrical Engineering, University Teknologi Mara, 40450, Shah Alam, Selangor, Malaysia (Tajjudin, N.; Rahiman, M.H.F.; Taib, M.N.)
Abstract	This paper presents the simulation and assessment of a Model Predictive Control (MPC) for the steam distillation essential oil extraction process. The mathematical model of the plant was obtained beforehand from the system identification technique by using ARX model structure. The model is then applied to the MPC control structure as a predicted model. The objective of the controller design is to keep low overshoot in steam temperature in order to improve the dynamic response of the essential oil extraction process. The conventional feedback controller is good in terms of accuracy and to attain the stability of the controlled variable but it is rather complicated when dealing with the nonlinear characteristic and slow process dynamic. This is an important criterion when we opt for MPC since steam temperature was known to exhibit a very large time delay. The simulation results on both PID and MPC show that the MPC can sustain the steam temperature at required set point efficiently with acceptable value of overshoot and RMSE.
Starting Page	446
Ending Page	449
File Size	188462
Page Count	4
File Format	PDF
ISBN	9781424451869
DOI	10.1109/SCORED.2009.5442977
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-16
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stability Optimized production technology Predictive models PID Nonlinear dynamical systems Adaptive control Model Predictive Control Petroleum Essential Oil System identification Temperature control Mathematical model Predictive control
Content Type	Text
Resource Type	Article

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