• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1163-1168
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• 2006

Manufacturing technology for the production of high value-added fine chemical products is emphasized and getting more attention as the diversified interests of customers and the demand of high quality products are getting bigger and bigger everyday. Thus, the development of advanced batch processes, which is the preferred and most appropriate way of producing these types of products, and the related technologies are becoming more important. Therefore, high-precision batch distillation is one of the important elements in the successful manufacturing of fine chemicals, and the importance of the process operation strategy with quality assurance cannot be overemphasized. Accordingly, proposing a process structure explanation and operation strategy of such processes including batch processes and batch distillation would be of great value. We investigate optimal operation strategy and production planning of multi-purpose plants consisting of batch processes and batch distillation for the manufacturing of fine chemical products. For the short-term scheduling of a sequential multi-purpose batch plant consisting of batch distillation under MPC and UIS policy, we proposed a MILP model based on a priori time slot allocation. Also, we consider that the waste product of being produced on batch distillation is recycled to the batch distillation unit for the saving of raw materials. The developed methodology will be especially useful for the design and optimal operations of multi-purpose and multiproduct plants that is suitable for fine chemical production.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.238-243
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• 1986

Distillation columns are widely used in almost every chemical plant. The use of multivariable control for such units is attractive because of the strong interactions exhibited between outputs and inputs and the desire to control simultaneously both top and bottom products. In this research design of a robust multivariable controller for distillation column was considered; output feedback controller with proportional and integral modes was designed using pole assignment. The transfer function matrix was obtained by fitting the step response realtions between single input double output pairs of variables. This matrix was then converted to linear time invariant state space model by multivariable realization technique. With the proposed multivariable proportional and integral controller applied to the process, the result of the digital computer simulation showed a good performance of asymtotic tracking. The limited experimental performance of this multivariable control was compared with the result from simulation. It was found that the proposed controller performed satisfactorily for the distillation column which separated binary mixture of methanol and water.

• Korean Chemical Engineering Research
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• v.47 no.3
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• pp.327-331
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• 2009

A thermally coupled distillation system is constructed using two columns used in a conventional two column system, and its operability is examined by investigating the dynamic behavior. For the control of three product specifications, the step response test is performed and a $3{\times}3$ control structure using flow rates of overhead and side products and vapor boilup is suggested. The performance of the proposed control system indicates that the specification control of bottom product is the most difficult but the operation of the proposed system is available.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.263-268
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• 2001

A new control scheme s proposed for the control of reactive batch distillation (RBD) column. A nonlinear wave model captures the essential dynamic behavior of the RBD process. The proposed control scheme is based on both Generic Model Control(GNC) and nonlinear wave model. The control scheme uses a profile position of the column as a controlled variable. Ethanol esterification process using RBD is chosen as an example process. Tight control of the distillate purity is obtained with the use of the proposed control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.461-467
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• 1998

In spite of significant nonlinearities even in the simplest model, some types of steady-state and dynamic behavior common for nonlinear systems have never been associated with distillation columns. In recent years, multiplicity of steady states has been a subject of much research and is now widely accepted. Subsequently, stability of steady states has been explored. Another phenomenon that. although widely observed in chemical reactors, has not been associated with models of distillation columns is the existence of periodic oscillations. In this article we study the steady-state and dynamic behavior of the azeotropic distillation of the ternary homogeneous system methanol-methyl butyrate-toluene. Our simulations reveal nonlinear behavior not reported in earlier studies. Under certain conditions, the open-loop distillation system shows a sustained oscillation associated with branching to periodic solutions. The limit cycles are accompanied by traveling waves inside the column. Significant underdamped oscillations are also observed over a wide range of product rates.

• Korean Chemical Engineering Research
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• v.48 no.6
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• pp.725-730
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• 2010

The fully thermally coupled distillation columns(FTCDC) are thermodynamically more efficient than conventional columns. Despite these advantages, industry has been reluctant to use FTCDC. This can be largely attributed to the lack of established design procedures and column operability. In this study, the $3{\times}3$control structure was applied to control the FTCDC which was simulated using Aspen HYSYS on the possible control structure of 4 kinds and control performance was investigated. As the result of dynamic simulations, one of the proposed structures had better controllability of product compositions and control efficiency was evaluated.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.240-245
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• 1990

A on-line optimization scheme based on model in a binary distillation process is proposed. A reduced-order model utilized the concept of collocation is used as a process model and the recursive prediction error method is employed to identify the reduced-order model. The concentrations of end products are controlled by nonlinear adaptive predictive control algorithm. The objective function is constructed to find optimum operate condition for saving utility cost. The proposed optimization is scheme is tested through simulation studies in 13-staged water-methanol distillation column.

• Korean Chemical Engineering Research
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• v.43 no.1
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• pp.39-46
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• 2005

Though a fully thermally coupled distillation column-an energy efficient distillation system-consumes less energy, it is not widely implemented in practice due to its operational difficulty. A 3-column distillation system having improved operability is proposed here, and its energy saving performance and application related issues are investigated from the implementation result to a practical hexane process. When an energy integration is employed, the proposed system requires 18% less energy than a conventional 2-column system, which is found from the HYSYS simulation. Though more control loops than the 2-column system are required, the proposed system has better controllability of product compositions and the pressure control of the system is easier.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.367-371
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• 1989

A linear form of reduced-order distillation model is proposed, which contains the physical properties of distillation process and can be used in real time applications. The proposed model is linear in terms of liquid mole fraction and contains some tuning parameters. To verify the applicability of the proposed model, the model identification using nonlinear filtering techniques was applied. As a result, it was found that this model represented the simulated distillation process very closely as the parameters were converged.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.99-104
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• 1991

An adaptive predictive control method for SISO and MIMO plants is proposed. In this method, future predictions of process output based on a bilinear CARIMA model are used to calculate the control input. Also, a classical recursive adaptation algorithm, equation error method, is used to decrease the uncertainty of the process model. As a result of the application on distillation process, the ability of the set-point tracking and the disturbance rejection is acceptable to apply to the industrial distillation processes.