• Bulletin of the Korean Chemical Society
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• v.14 no.6
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• pp.759-762
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• 1993

• Bulletin of the Korean Chemical Society
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• v.22 no.12
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• pp.1299-1300
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• 2001

• Korean Journal of Pharmacognosy
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• v.22 no.2
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• pp.124-127
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• 1991

In the preceding paper, it was reported that total 63 traditional Korean herbal medicines listed in the Korean Pharmacopoeia and Korean Natural Drug Standards were found to be different plants in terms of systematic botany when those were compared with other two countries' drug compendia, Chinese Pharmacopoeia, Japanese Pharmacopoeia and Japanese Natural Drug Standards. Among 63 traditional Korean herbal drugs, 28 items were subject to the chemical identification test by using official methods that are described in the Korean Pharmacopoeia and the Korean Natural Drug Standards. In addition, 5 items were also tested by using the official methods described in Chinese and Japanese drug compendia, since there are no official chemical tests available in the Korean drug compendia. It was found that most of chemical tests appeared to be suitable. It was noted that the chemical test for Atractylodis Rhizoma(蒼朮) was incorrect and unapplicable. Those chemical tests for Clematidis Radix(威靈仙), Rubi Fructus(覆盆子) and Viticis Fructus(蔓荊子) are desirable to be revised for more accurate identification.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2600-2605
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• 2003

The PBL (Poly-butadiene Latex) production process is a typical batch process. Changes of the reactor characteristics due to the accumulated scaling with the increase of batch cycles require adaptive tuning of the PID controller being used. In this work we propose a tuning method for PID controllers based on the closed-loop identification and the genetic algorithm (GA) and apply it to control the PBL process. An approximated process transfer function for the PBL reactor is obtained from the closed-loop data using a suitable closed-loop identification method. Tuning is performed by GA optimization in which the objective function is given by ITAE for the setpoint change. The proposed tuning method showed good control performance in actual operations.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.344-350
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• 1996

An adaptive predictive level control of waste heat steam boiler was studied by using mathematical models considering the inverse response. The simulation experiments of the model identification were performed by using linear and bilinear models. From the results of simulations it was found that the bilinear model represented the actual dynamic behavior of steam boiler very well. ARMA model was used in the model identification and the adaptive predictive controller. To verify the performance and effectiveness of the adaptive predictive controller used in this study the simulation results of the adaptive predictive level control for waste heat steam boiler based on bilinear model were compared to those of P, PI and PID controller. The results of simulations showed that the adaptive predictive controller provides the fast arrival to setpoint of liquid level.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.3-26
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• 2001

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the cross correlation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is ...

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1204-1209
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• 1990

This paper offers the theory and method for regression analysis of the regression model with operational parameter variables based on the fundamentals of mathematical statistics. Regression coefficients are usually constants related to the problem of regression analysis. This paper considers that regression coefficients are not constants but the functions of some operational parameter variables. This is a kind of method of two-step fitting regression model. The second part of this paper considers the experimental step numbers as recursive variables, the recursive identification with unknown operational parameter variables, which includes two recursive variables, is deduced. Then the optimization and the recursive identification are combined to obtain the sequential experiment optimum design with operational parameter variables. This paper also offers a fast recursive algorithm for a large number of sequential experiments.

• Journal of the Korean Chemical Society
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• v.7 no.2
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• pp.106-114
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• 1963

The products from polymer pyrolysis at $450^{\circ}$ are cooled with ice, then liquid and gaseous portions are analysed by gas chromatography. Di-2-ethyl hexyl sebacate column, silicone oil column, silica gel column and tetraethyleneglycol dimethylether column, which was most effective for the separation of hydrocarbon gases, are used. Identification of isomers could be secured more effectively by gas chromatography than mass spectrometry. Elucidation of the mechanism for thermal decomposition of polymers could be done through the identification of pyrolysis products. Although more extensive work is needed, some patterns of polymer pyrolysis are discussed.

• Journal of the Korean Chemical Society
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• v.7 no.2
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• pp.115-121
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• 1963

Aliphatic hydrocarbon gases from rubber pyrolysis have been identified by gas chromatography with tetraethyleneglycol dimethylether column. Rubbers used in this work are polyisoprene, SBR, NBR, polybutadiene, buthyl rubber, polychloroprene and polyurethane rubber. The chromatogram is characteristic for each polymer. Author proposes a method of identification of synthetic rubbers by gas chromatograph of pyrolyzed gas. Sample is pyrolyzed at $450^{\circ}C$ under nitrogen or more effectively helium and gaseous portion, which eliminated liquid condensate, is passed to the column. The appearance of exclusively large peak of isoprene, isobutylene and carbon dioxide shows the presence of polyisoprene, polyisobutylene and polyurethane, respectively. Large peak of butadiene will appear in case of polybutadiene, SBR and NBR, but SBR can be identified through the styrene peak in gas chromatogram of liquid pyrolyzate and NBR can be identified by the evolution of hydrogen cyanide during pyrolysis. Polychloroprene is identified by the evolution of hydrogen chloride. This method could be applied to the identification of copolymer or polymer blend.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2004.11a
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• pp.221-232
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• 2004

Paper process is complex and multivariable system. Identification of a paper process model is imperative for the development of predictive control method. 13-level Pseudo-Random Sequence Signals were used to identify the plant model in which the neural network model was considered model as a real paper process. Results of simulations for identification using 13-level PRS signals and Prediction Error Method are compared with plant operation data. From the comparison, we can see that the dynamics of the model show good agreement with those of real plant.