Composition control and temperature inferential control of dividing wall column based on model predictive control and PI strategies

The dividing wall column （DWC） is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control （MPC） is an advanced control strategy that has acquired extensive applications in various industries. In this study, MPC is applied to the process for separating ethanol, n-propanol, and n-butanol ternary mixture in a fully thermally coupled DWC. Both composition control and tem- perature inferent/al control are considered. The multiobjective genetic algor/thm function ＂gamult/obj＂ in Matlab is used for the weight tuning of MPC. Comparisons are made between the control performances of MPC and PI strategies. Simulation results show that although both MPC and PI schemes can stabilize the DWC in case of feed disturbances, MPC generally behaves better than the PI strategy for both composition control and tempera- ture inferential control, resulting in a more stable and superior performance with lower values of integral of squared error （ISE）.

Enhanced temperature difference control of distillation columns based on the averaged absolute variation magnitude

Temperature difference control(TDC)schemes can clearly suppress the adverse influence of pressure variations on product quality control of various distillation columns(DCs)by employing temperature differences(TDs)between the sensitive stage temperature(T_(S))and reference stage temperature(T_(R)),i.e.,T_(S)-T_(R),to infer the controlled product qualities.However,because the TDC scheme has failed to specially take the corresponding relationship between the TD employed in each control loop and the controlled product quality into account,it may suffer from relatively large steady-state errors in the controlled product qualities.To address this problem,an enhanced TDC(ETDC)scheme is proposed in the current article,in which an enhanced TD(ETD),i.e.,T_(S)-α×T_(R),is employed to replace the conventional TD for each control loop.While the locations of the sensitive and reference stages of the ETD are respectively determined according to sensitivity analysis and SVD analysis,the adjusted coefficientαis set to be the ratio between the averaged absolute variation magnitudes(AAVMs)of the T_(S)and T_(R)so that the relationship between the T_(S)and T_(R)can be appropriately coordinated.With reference to the operations of three different distillation systems,i.e.,one conventional DC distilling an ethanol(E)/butanol(B)binary mixture,one conventional DC distilling an E/propanol(P)/B ternary mixture,and one dividing-wall distillation column distilling an E/P/B ternary mixture,the performance of the ETDC scheme is assessed by compared with the conventional TDC scheme and the double TD control(DTDC)scheme.The dynamic simulation results show that the ETDC scheme is better than the conventional TDC scheme with reduced steady-state errors in the controlled product qualities and improved dynamic responses,and is comparable with the DTDC scheme despite the less temperature measurements are employed.

Actuator Fault Monitoring and Fault Tolerant Control in Distillation Columns

This paper presents, from a practical viewpoint accommodation in distillation columns. Addressing faults in an investigation of real-time actuator fault detection, propagation and industrial processes, coupled with the growing demand for higher performance, improved safety and reliability necessitates implementation of less complex alternative control strategies in the events of malfunctions in actuators, sensors and or other system components. This work demonstrates frugality in the design and implementation of fault tolerant control system by integrating fault detection and diagnosis techniques with simple active restructurable feedback controllers and with backup feedback signals and switchable reference points to accommodate actuator fault in distillation columns based on a priori assessed control structures. A multivariate statistical process monitoring based fault detection and diagnosis technique through dynamic principal components analysis is integrated with one-point control or alternative control structure for prompt and effective fault detection, isolation and accommodation. The work also investigates effects of disturbances on fault propagation and detection. Specifically, the reflux and vapor boil-up control strategy used for a binary distillation column during normal operation is switched to one point control of the more valued product by utilizing the remaining healthy actuator. The proposed approach was implemented on two distillation processes： a simulated methanol-water separation column and the benchmark Shell standard heavy oil fractionation process to assess its effectiveness.