Pichak Tanakunmas. NARX base analytical model predictive controller design under integrated software environment : application to ethylene dichloride distillation conlumn. Master's Degree(Chemical Engineering). Kasetsart University. Office of the University Library. : Kasetsart University, 2017.
NARX base analytical model predictive controller design under integrated software environment : application to ethylene dichloride distillation conlumn
Abstract:
This work presents a new technique to design a model-based controller for a high purity distillation column that also integrate the use of chemical process simulator (Aspen Plus Dynamics®) into modeling and evaluating closed-loop performance. An ethylene dichloride distillation unit is considered as a case study of high purity distillation. The proposed controller is formulated by combining the analytical model predictive control (AMPC) with nonlinear autoregressive with an exogenous (NARX) model. The firstorder compensator is added to the control system to eliminate the offset from process/model mismatch. The Aspen Plus Dynamics process flowsheet simulator is applied to construct distillation modeling in controller design for taking into account the non-ideal system behaviors. The control objective is to handle the pressure at the top of the column and the composition of distillate/bottom products by adjusting the flow cooling water, reflux flow rate, and reboiler duty, simultaneously. The control performance of the proposed method is compared with the industrial traditional control such as proportional-integral (PI) control under servo/regulatory tests and integrated software simulation environment between Aspen plus dynamics and MATLAB/Simulink software simulator. The simulation results show that the proposed control method has better performance in multi-setpoint tracking control than the traditional one and can handle well in the input disturbances rejection (i.e. fluctuated in feed flow and feed composition). Moreover, the proposed controller can take care of the energy consumption together with multivariable control at all desired setpoints.
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