• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.83-86
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• 1998

In this paper, a fuzzy model based on the Polynomial Neural Network(PNN) structure is proposed to estimate the emission pattern for air pollutant in power plants. the new algorithm uses PNN algorithm based on Group Mehtod of Data Handling (GMDH) algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the least square method in order to identify the optimal consequence parameters. Both time series data for the gas furnace and data for the NOx emission process of gas turbine power plants are used for the purpose of evaluating the performance of the fuzzy model. The simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.633-635
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• 2009

It is a quite quality concerning to control temperature of single crystalline growth as it does when you get most of heat treating products. It is also important factor to control temperature when you make the $Al_2O_3$(single crystalline) used to artificial jewels, glass of watches, heat resistant transparent glasses. Thus, it is a major interest to get the proper temperature in accordance with the time process while you are making mixture of oxygen and hydrogen to have the right temperature. In this paper, we will study of electrical valve positioning system for the gas mixture to improve the quality of products.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.259-262
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• 1997

In this paper, a fuzzy model based on the polynomial Neural Network(PNN) structure is proposed to estimate the emission pattern for air pollutant in power plants. The new algorithm uses PNN algorithm based on Group Method of Data Handling (GMDH) algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the least square method in order to identify the optimal consequence parameters. Both time series data for the gas furnace and data for the NOx emission process of gas turbine power plants are used for the purpose of evaluating the performance of the fuzzy model. The simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy anhd feasibility than other works achieved previously.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.129-134
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• 1992

Fuzzy theory has shown good control performance for non-linear system that is difficult to be controlled by the conventional controller. Backpropagation neural network can interpolate output without the priori knowledge of its dynamics. In this paper, we proposes a Fuzzy-Neural Controller. The Fuzzy Control by deterministic rule may not be sensitive for uncertain conditions and has a disadvantage of setting the rule by repeatedly experience. To solve such problems, we construct Self organizing Fuzzy-Neural Controller which can reorganize the fuzzy rule according to the state of system. Experimental results show that proposed Fuzzy-Neural Controller has better performance than conventional controller(PID) has especially rising time and overshoot characteristics.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.7
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• pp.967-975
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• 2000

Transient characteristics of a boiler and turbine system for a steam power plant are simulated. One-dimensional unsteady models are introduced for each component. An interaction between boiler and turbine and a control of the water level in the drum are taken into account. Transient responses of the system to the variations of main system variables such as fuel and air flow rate, cooling water injection rate at the attemperator, gas recirculation rate at the furnace and opening of the turbine control valve are examined. Effect of fluid inertia and tube wall thermal inertia on predicted dynamic behavior is investigated.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.395-397
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• 1996

The existing CPC(Center Position Controller) has unstably performed because of dusts on reflection panel, CCD protector contamination due to high temperature in furnace or other parameters. The reason is that the existing CPC has a Z80 processor as a CPU and only performs low level image processing as a simple edge detector. So the improvement of control system through the development of robust edge detection algorithm overcoming changes of measuring environment is needed. For this, in this study we carefully analyze the image of the strip rolled in occasion that measuring environment is changing, develop the optimal edge detection algorithm to solve the problems, generate the control signal suitable for the existing CPC(Center Position Controller), and propose the capability of application to the actual environment.

• Proceedings of the KIPE Conference
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• 2010.11a
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• pp.234-237
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• 2010

This paper proposes a balancing control of DC-link voltages of a H-bridge multilevel inverter for STATCOM application. Individual DC link voltage is controlled by simply adjusting the d-q voltage reference through a PI controller in each cell while the main controller carries out the reactive power control. The correctness and effectiveness of the method are validated by PSIM simulation with unbalanced load condition data taken from a typical arc furnace load, showing the adverse effects of load unbalance to DC link voltage significantly suppressed.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.1
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• pp.19-30
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• 2015

A static synchronous compensator (STATCOM) applied to rapidly changing, highly unbalanced loads such as electric arc furnaces (EAFs), requires both positive-sequence and negative-sequence current control, which indicates fast response characteristics and can be controlled independently. Furthermore, a delta-connected STATCOM with cascaded H-bridge configuration accompanying multiple separate DC-sides, should have high performance zero-sequence current control to suppress a phase-to-phase imbalance in DC-side voltages when compensating for unbalanced load. In this paper, actual EAF data is analyzed to reflect on the design of current controllers and a pioneering zero-sequence current controller with a superb transient performance is devised, which generates an imaginary -axis component from the presumed response of forwarded reference. Via simulation and experiments, the performance of the positive, negative, and zero-sequence current control of a cascaded H-bridge STATCOM for EAF is verified.

• Journal of the Korea Concrete Institute
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• v.14 no.3
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• pp.409-419
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• 2002

Nowadays, antiwashout underwater concrete is widely used for constructing underwater concrete structures but they, especially placed in marine environment, can be easily attacked by chemical ions such as SO$\^$2-/$\_$4/ Cl$\^$-/ and Mg$\^$2＋/, so the quality and capability of concrete structures go down. In this paper, to solve and improve those matters, flyash and GGBFS(ground granulated blast furnace slag) were used as partial replacements for ordinary portland cement. As results of experiments for fundamental properties of antiwashout underwater concrete containing 10, 20, 30％ of flyash and 40, 50, 60 ％ of GGBFS respectively, setting time, air contents, suspended solids and pH value were satisfied with the "Standard Specification of Antiwashout Admixtures for Concrete" prescribed by KSCE, and also slump flow, efflux time and elevation of head were more improved than that of control concrete. From the compressive strength test, it was revealed that the antiwashout underwater concrete containing mineral admixtures(flyash and GGBFS) is more effective for long term compressive strength than control concrete. An attempt to know how durable when they are under chemical attack has also been done by immersing in chemical solutions that were x2 artificial seawater, 5 ％ sulphuric acid solution, 10％, sodium sulfate solution and 10％ calcium chloride solution. After immersion test for 91days, XRD analysis was carried out to investigate the reactants between cement hydrates and chemical ions and some crystalline such as gypsum ettringite and Fridel′s salt were confirmed.

• Journal of Korea Foresty Energy
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• v.22 no.1
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• pp.37-43
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• 2003

The influence factors for char yield in the carbonization process of natural cellulose are the carbonization temperature, the heating rate and the atmosphere in the furnace. In general, it is well known that the improvement of char yield is expected under the conditions of the lower carbonization temperature, the slower heating rate and the presence of inert gas in the furnace. In this study, it has been investigated the effect of the heating rate control with sulfuric acid as a dehydrating agent for the improvement of char yield in the carbonization process of natural cellulose. The cellulose treated with sulfuric acid has shown the weak dependency of heating rate in char yield, whereas the untreated cellulose has shown the strong dependency. These findings clearly suggest that it can be useful to control heating rate with appropriate dehydrating agent in the carbonization process to improve the char yield and shortening the carbonization time.