• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1638-1639
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• 2007

This paper proposes an adaptive Dynamic Matrix Control (DMC) using Fuzzy Inference and its application to boiler-turbine system. Nine Step Response Models (SRM) at various operating points are represented as fuzzy inference rules. On-line fuzzy inference is performed at every sampling step to find the suitable SRM. Therefore, the proposed adaptive DMC can consider the nonlinearity of boiler-turbine system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.687-692
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• 1991

To reduce the complexity in constructing a fuzzy logic controller of multivariable systems, three major methods are presented. One is the method of constructing single-input-single-output fuzzy logic controllers after decoupling the target system. Another is the method of using fuzzy relation matrices which indicate the relation between each input and output. The other is the method of using the hierarchically classified inputs which dominantly influence one output than other inputs. Using the last two methods, simulation results of fuzzy logic controller implemented on 160MW boiler-turbine plant model are also shown.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.83-86
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• 1995

This paper proposes an auto-tuning method of feedforward signal in boiler control of thermal power plants by using the neural network. The neural network produces an optimal feedforward signal by tuning the weights of the network. The weights are adapted effectively by using the teaching signal of PI control output. The proposed method was evaluated based on a detailed simulator which expressed non-linear characteristics of the 600 MW actual thermal power plant at load chaning operations, showed effectiveness in the learning of the weights of the neural network, and gave an accurate control performance in the temperature control of the system. Through the evaluation, the proposed method was proved to be effectively applicable to the actual thermal plants as the automatic adjustment tool.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.287-288
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• 2007

This paper is for a Real-time Active Control System to operate a boiler. By sensing of flame we wanted to get status of a furnace as many as possible, like load, efficiency, and/or amount of pollutant. These data can be used to make optimal running point by controlling the ratio of air and fuel. So the last object is to make a closed actual control loop from optical head to valve controllers. The first job was to design and to develop a optical data acquisition system. including optical sensor module. And we gathered flame data in variable situations for taking the trend of flame against burning environment. Currently we are developing a general system model, designing some control strategy and testing this active control system.

• 대한기계학회논문집
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• 제16권5호
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• pp.965-973
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• 1992

본 연구에서는 산업용 가스전소자연순환보일러를 모델로 선정하여 이 모델에 영향을 주는 인자에 대하여 동적 해석을 하였다. 수위와 압력을 연결한 자연순환 보일러의 제어를 위한 총괄적인 블록 선도를 제시하였고, 이 선도를 토대로 전산프로 그램을 개발하고 계산치와 실제 측정치를 비교, 검토하여 이론 해석상의 모순이 없음 을 확증하였다. 연구결과를 산업용 자연순환 gas 보일러의 설계에 응용하도록 하여 보일러의 동특성을 제시하고 이것에 의한 전제어시스템의 신속하고 정확한 설계치를 제시하여 응용사용토록 하여 무엇보다도 전보일러시스템의 안전운전과 경제성(제작비 및 가동비)을 제고하는데 있다. 본 논문을 제1부, 제2부로 나누어 발표해야 하므로 제1부는 결론을 포함시키지 못하며 제2부에서 결론을 제시하겠으니 참조하여 주시기 바랍니다.

• 전자공학회논문지B
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• 제31B권10호
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• pp.53-66
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• 1994

In this paper, a fuzzy expert system is developed for fault diagnoisis of a drum-type boiler system in fossil power plants. The develped fuzzy espert system is composed of knowledge base, fuzzification module, knowledge base process module, knowledge base management module, inference module, and linguistic approximation module. The main objective of the fuzzy expert system is to check the states of the system including the drum level and detect faults such as the feedwater flow sensor fault, feedwater flow control valve fault, and water wall bube rupture. The fuzzy expert system diagnoses faults using process values, manipulated values, and knowledge base which is built via interviews and questionaries with the experts on the plant operations. Finally, the validity of the developed fuzzy expert system is shown via experiments using the digital simulator for boiler system is Seoul Power Plant Unit 4.

• 전기학회논문지
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• 제59권11호
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• pp.2006-2011
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• 2010

The superheater in the thermal power plant makes the wet steam into the dry steam with high temperature and high pressure by using the boiler heat. The dry steam pressure rotates the turbine-generator system. The efficiency and life time of the boiler heavily depends on the steam temperature regulation. The steam temperature can be deviated from the reference by the MW demand of the power plant. It is therefore required that the PI(proportional-integral) controller should be robust against the disturbance such as the MW demand. In this paper, the PI controller with the integral state predictor is proposed and applied to regulate the steam temperature of the superheater, and it is compared with the conventional PI controller operated in the thermal power plant in view of control performance.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.450-454
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• 1997

This system is the automatic boiler tube bending equipment which has four heads for bending the tube and the carriage for moving the tube. The system consists of two frames for transporting each moving parts, high-frequency heating equipment for heating the tube in hot bending, control panel for inputting the job data operating, remote control unit for concetration and distribution of input/output, and the monitoring system which can establish unmanned operationby receiving the bending job data via LAN form a design teamwhich produces the job data and schedule based on master production plan and diagnoses bending data change, input, whole system status, and system malfunctions. By employing this system, 30% of production improvement was achieved was achieved comparing to the existing bending system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1449-1454
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• 2003

For many industrial processes there are good static models used for process design and steady state operation. By using system identification techniques, it is possible to obtain black-box models with reasonable complexity that describe the system well in specific operating conditions [1]. But black-box models using inductive modeling(IM) is not suitable for model based control because they are only valid for specific operating conditions. Thus we need to use deductive modeling(DM) for a wide operating range. Furthermore, deductive modeling is several merits: First, the model is possible to be modularized. Second, we can increase and decrease the model complexity. Finally, we are able to use model for plant design. Power plant must be able to operate well at dramatic load change and consider safety and efficiency. This paper proposes a simplified nonlinear model of an industrial boiler, one of component parts of a power plant, by DM method and applies optimal control to the model.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.283-285
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• 2002

Boiler combustion systems are large, non-linear systems with numerous interactions between its component parts. In the analysis of such complex systems. dynamic simulation is recognized as a powerful method of keeping track of the myriad of interactions. This paper shows and discusses the developed analysis model, such as the forced draft fan the primary air fan, the furnace and burner system, pulverizer, air preheater and induced draft fan, etc. in accordance with BMCR condition of boiler using the Modular Modeling System(MMS) software.