• Korean Chemical Engineering Research
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• 제52권5호
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• pp.587-591
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• 2014

고급 홍삼의 생산 수율을 증가시키는 제어 방법에 관한 실험을 수행하였다. 수삼에서 홍삼을 만드는 과정 중 수증기로 수삼을 찌는 증삼 공정에서 동체균열, 내공, 내백 등이 발생하는데 이는 홍삼의 품질을 저하시키는 원인이 된다. 고급 홍삼의 수율을 증가시키기 위해서는 이런 불량 요인을 최소화하는 방법이 필요하다. 최근까지 대부분의 증삼 공정의 제어는 증삼 과정의 필수 인자인 온도만을 조절하거나 온도와 압력을 동시에 조절하여 제어하는 방법이 연구되었다. 그러나 이는 불량 요인을 최소화하는 목적에 적합하지 못한 것으로 보인다. 이와 달리, 본 연구에서는 기존의 홍삼 제조 방식을 토대로 $96{\sim}99^{\circ}C$의 온도를 유지하면서 수삼의 무게 제어를 통하여 불량 요인을 최소화하는 제어 방법을 제시한다. 무게 제어를 적용한 실험 결과 증삼 과정 후 수삼의 동체균열의 불량요인이 줄어드는 것을 확인할 수 있었다.

• 한국산학기술학회논문지
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• 제12권4호
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• pp.1812-1816
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• 2011

본 연구에서는 약액 주입 후 미 도포로 인한 복합적인 공정불량을 예방하기 위하여 100nm 이하의 나노 반도체 제조공정에서 필수적인 스피너(spinner) 장비를 위한 약액 흐름제어 시스템을 개발하였다. 본 연구개발을 통하여 실시간으로 상태요소들을 감시할 뿐만 아니라 상태요소의 비정상적 변화나 웨이퍼 가공불량이 발생할 경우 해당 유니트를 정지시킴과 동시에 원격지에 있는 엔지니어에게 경보를 전송함으로써 즉각적인 대처가 가능하여 모듈의 수율을 향상시킬 수 있을 것으로 기대된다. 또한 세부 동작 시퀀스를 제어하기 위한 H/W와 S/W 시스템을 생산라인에 실장하고 성능점검 및 인증을 수행한 결과 5가지의 유형별 비정상적 프로세스를 정확히 검출하였다.

• 제어로봇시스템학회논문지
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• 제12권12호
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• pp.1178-1183
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• 2006

This paper is concerned with the modeling and identification of pH neutralization process as nonlinear chemical system. The pH control has been applied to various chemical processes such as wastewater treatment, chemical, and biochemical industries. But the control of the pH is very difficult due to its highly nonlinear nature which is the titration curve with the steepest slope at the neutralization point. We apply SVM which have become an increasingly popular tool for machine teaming tasks such as classification, regression or detection to model pH process which has strong nonlinearities. Linear and radial basis function kernels are employed and each result has been compared. So SVH based on kernel method have been found to work well. Simulations have shown that the SVM based on the kernel substitution including linear and radial basis function kernel provides a promising alternative to model strong nonlinearities of the pH neutralization but also to control the system.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2001년도 춘계학술대회 논문집
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• pp.217-220
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• 2001

In the shearing process the burr or rollover must be minimized in order to improve the quality of product. The burr size can be minimized by control of several process parameters. But removal of all burrs are impossible. Most mechanical type deburring methods (vibrating bowls, rotating barrels, shot blasting, for example.) will remove large burrs, other methods use chemical (electro-chemical deburring) or heat (thermal energy deburring). The electro-chemical deburring process removes burrs by the deplating method. Electro-chemical deburring equipment is requires a small capital investment than other methods(mechanical or thermal methods). Electro-chemical deburring method need to many parameters for control such as a time, voltage and concentration of electrolyte. In this paper shows relations of these parameters by experiment.

• Korean Chemical Engineering Research
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• 제50권5호
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• pp.815-824
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• 2012

분리할 성분들의 비점이 비슷하거나 공비를 형성하는 경우 일반적인 증류로 완전 분리가 불가능하다. 이를 극복하기 위하여 제 3성분을 가하여 상대 휘발도에 변화를 주는 추출 증류가 사용된다. 일반적으로 두 개의 증류탑으로 이루어진 추출 증류 공정이 사용되나 열 통합된 연속식 증류탑으로 이루어진 추출 열 통합 증류 공정은 보다 에너지 효율이 높고 장치비가 절감되는 장점을 가지고 있다. 그러나 추출 열 통합 증류 공정은 종래의 추출 증류 공정에 비하여 운전 및 제어가 어려워 널리 사용되지 못하고 있다. 본 논문에서는 이러한 단점을 극복할 수 있도록, 또한 외란에 대하여 안전한 조업이 이루어지도록 할 목적으로 최적 조업조건에서의 추출 열 통합 증류 공정의 운전 및 제어를 연구하였고 여러 가지의 제어 구조를 제안하였다. 제안된 제어구조 중에 프로필 위치 제어가 가장 좋은 제어 성능을 나타내었다.

• 제어로봇시스템학회논문지
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• 제13권11호
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• pp.1128-1136
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• 2007

This paper presents an application study of a model predictive control based commercial package PCTP to real chemical processes. The first case study concerns a product purity control of a splitter process which distillates styrene from undesired component ethyl-benzene produced from ethyl-benzene dehydrogenation reaction. The second case study is about a temperature control of ethyl-benzene dehydrogenation reactor and an excess oxygen control of the fired heater. Optimum control structure for MPC application is developed for each case study. The application results show a significant improvement in control performance and stability.

• 한국안전학회지
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• 제24권1호
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• pp.31-36
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• 2009

This paper focuses on techniques of improving refinery reliability, availability, and profitability. Our team developed a corrosion control document(CCD) for processing of the crude distillation unit(CDU). Recent study shows the loss due to corrosion in US is around $276 billion. It's a big concern for both managers and engineers of refinery industry. The CCD consists of numerous parts namely damage mechanism(DM), design data, critical reliability variable(CRV), guidelines, etc. The first step in the development of CCD is to build material selection diagram(MSD). Damage mechanisms affecting equipments and process need to be chosen carefully based on API 571. The selected nine DM from API 571 are (1) creep/stress rupture, (2) fuel ash corrosion, (3) oxidation, (4) high temperature sulfidation, (5) naphthenic acid corrosion, (6) hydrochloric acid(HCL) corrosion, (7) ammonium chloride(salt) corrosion, (8) wet $H_2S$ corrosion, and (9) ammonia stress corrosion cracking. Each DM related to corrosion of CDU process was selected by design data, P&ID, PFD, corrosion loop, flow of process, equipment's history, and experience. Operating variables affecting severity of DM are selected in initial stage of CRV. We propose the guidelines for reliability of equipments based on CRV. The CCD has been developed on the basis of the corrosion control in refinery industry. It also improves the safety of refinery process and reduces the cost of corrosion greatly.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.344-349
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• 1990

Under the assumption that process input/output data are sufficiently rich to allow reasonable plant identification, a long-range predictive control method for SISO bilinear plant is derived. In order to ensure offset-free behaviour of the control method, a new bilinear CARIMA model with variable dead-time is introduced. Furthermore, to extend the maximum output prediction horizon, the future predicted outputs in the bilinear term are assumed to be equal to the known future set-points. With a classical recursive adaptation algorithm, the proposed control scheme is capable of stable control of bilinear plants with variable parameters, with variable dead-time, and with a model order which changes instantaneously. Several simulation results demonstrate the characteristics of the proposed bilinear model predictive control method.

• International Journal of Control, Automation, and Systems
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• 제2권3호
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• pp.263-278
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• 2004

This paper reviews dynamic programming (DP), surveys approximate solution methods for it, and considers their applicability to process control problems. Reinforcement Learning (RL) and Neuro-Dynamic Programming (NDP), which can be viewed as approximate DP techniques, are already established techniques for solving difficult multi-stage decision problems in the fields of operations research, computer science, and robotics. Owing to the significant disparity of problem formulations and objective, however, the algorithms and techniques available from these fields are not directly applicable to process control problems, and reformulations based on accurate understanding of these techniques are needed. We categorize the currently available approximate solution techniques fur dynamic programming and identify those most suitable for process control problems. Several open issues are also identified and discussed.