• Transactions on Control, Automation and Systems Engineering
• /
• v.2 no.3
• /
• pp.196-200
• /
• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used fur on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

• Transactions on Control, Automation and Systems Engineering
• /
• v.2 no.2
• /
• pp.136-139
• /
• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used for on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.209-211
• /
• 1986

The continuous time linear quadratic problem (LQP) has been applied to the control of a 8-tray distillation column using the code VASP. The weighting matrices for the state variables and control variables were adjusted iteratively. The simulation results of the optimal control with 2 inputs and 2 outputs showed that the LQP method is very satisfactory for a rapid response and feedback control, and any desired response could be obtained by adjusting the weighting matrices Q under = and R under =. The feedback gain matrix K under = was also determined.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.234-239
• /
• 1990

A neural controller for process control was proposed that combines a simple feedback controller with a neural network. This control was applied to distillation control. The feedback error learning technique was used for on-line learning. Important characteristics on neural controller were analyzed. The proposed neural controller can cope well with strong interactions, significant time delays, sudden changes in process dynamics without any prior knowledge of the process. It was shown that the neural controller has good features such as fault tolerance, interpolation effect and random learning capability

• Journal of Korean Society of Water and Wastewater
• /
• v.30 no.3
• /
• pp.343-350
• /
• 2016

Membrane distillation (MD) is a novel separation process that have drawn attention as an affordable alternative to conventional desalination processes. However, membrane fouling and pore wetting are issues to be addressed prior to widespread application of MD. In this study, the influence of ultrasonic irradiation on fouling and wetting of MD membranes was investigated for better understanding of the MD process. Experiments were carried out using a direct contact membrane distillation apparatus Colloidal silica was used as a model foulants in a synthetic seawater (35,000 mg/L NaCl solution). A vibrator was directed attached to membrane module to generate ultrasonic waves from 25 kHz (the highest energy) to 75 kHz (the lowest energy). Flux and TDS for the distillate water were continuously monitored. Results suggested that ultrasonic irradiation is effective to retard flux decline due to fouling only in the early stage of the MD operation. Moreover, wetting occurred by a long-term application of ultrasonic rradiation at 75 kHz. These results suggest that the conditions for ultrasonic irradiation should be carefully optimized to maximize fouling control and minimize pore wetting.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.295-298
• /
• 1996

In distillation column control, secondary measurements such as temperatures and flows are widely used in order to infer product composition. This paper addresses the design of static estimators using the secondary measurements for estimating the product compositions of the multicomponent distillation columns. Based on the unified framework for the estimator problems, the relationships among several typical static estimators are discussed including the effect of the measured inputs. Design guidelines for the composition estimator using PLS regression are also presented. The estimator based on the guidelines is robust to sensor noise and has a good predictive power.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.8
• /
• pp.3774-3778
• /
• 2012

A dynamic simulation of a fully thermally coupled distillation is conducted for the design of a possible operation scheme, and its performance is examined with an example process of reformate fractionation process. The outcome of the dynamic simulation indicates that the column can be operated by using a $3{\times}3$ control structure. The structure consists of three controlled variables of the compositions of overhead, side products and bottom and three manipulated variables of the flow rate of reflux, liquid split ratio between a main column and a prefractionator and steam.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1766-1769
• /
• 1997

Fast and accurate distillation design requires a model that significantly reduces the problem size withour loss of accruacy is especially suitable for rela-time applicatoins. the reduced order model is obtained by use of Principal Component Anlysis(PCA). Then the extended Kalman filter and the Recursie Predictiuon Error(RPE) mehtod are appliced to identify the model parameters and the feed compostion form the measuremenets of the coumn. as a consequence it is found that the model reduction thechique can account for the dynamics of the rigorous distillation model and not only the model parameters, bu also the feed compostion can be identified efficiently. this technique is applied to industrial operation data verify the performance of reduced order model.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1826-1829
• /
• 2003

Fine chemical production must assure high-standard product quality as well as characterized as multi-product production in small volumes. Installing high-precision batch distillation is one of the common elements in the successful manufacturing of fine chemicals, and the importance of the process operation strategy with quality assurance cannot be overemphasized. In this study, we investigate the optimal operation strategy and production planning of a sequential multi-purpose plants consisting of batch processes and batch distillation with unlimited intermediate storage. We formulated this problem as an MILP model. A mixed-integer linear programming model is developed based on the time slot, which is used to determine the production sequence and the production path of each batch. Illustrative examples show the effectiveness of the approach.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.466-470
• /
• 1988

A tunable reduced-order distillation model is proposed for real-time applications. To develop the model, a binary distillation column with MaCabe-Thiele assumptions was considered first and then the governing equations for the column were reduced to a simplified vector differential equations using the collocation method combined with cubic spline interpolation function. The final reduced-order model has four tuning parameters, relative volatilities and liquid holdups for rectifying and stripping sections, respectively. To assess the applicability of the developed model,the real-time adjustment of the model was tried by recursively updating the tuning parameters using the BKF algorithm. As a result, it was found that the reduced-model follows the simulated distillation process very closely as the parameters are improved.