• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.146-156
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• 2003

Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.6 no.2
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• pp.1-7
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• 2010

The objective of this study is to find the optimal control algorithm of a hybrid Plant, which is combined by renewable energy plant of the GSHP(Geothermal Source Heat Pump) and the normal plant (Chiller, boiler). The work presented in this study was carried out in the EnergyPlus(Version 2.0). The EnergyPlus was modified in order to simulate the hybrid plant. The plant system was controlled by the load-range-based operation in which schemes select a user specified set of equipment for each user specified range of a particular simulation condition. In the use of the load-range-based operation, four kind of control cases were defined and simulated in order to obtain the optimal control algorithm of the hybrid plant. The result showed that the Case 2 was the optimal control algorithm which used the GSHP as a base operating plant and the normal plant as an assistant operating plant. Even though the normal plant was operated in full load and the renewable energy plant of the GSHP was operated in partial load, the annual energy consumption of the normal plant was larger than that of the GSHP plant.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.450-453
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• 1996

This research presents a new method of detecting and diagnosing faults of a power plant. Detection of characteristic wave patterns from multichannel instrumentation signals forms the basis of the proposed approach. The dynamics of 500MW drum-type boiler (Boryung coal-fired plant unit #1 and #2) and its control systems are modeled and simulated to generate diverse operation patterns and fault situations and to utilize them for the development of the fault detection algorithms. The results of the boiler system modeling and simulations show a fairly high agreement when compared with some of the actual plant performance test data.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.349-352
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• 1991

Fuzzy modelling is a useful method when the variation of plant dynamics is large. In the fuzzy modelling by parameter identification, a new method is proposed in the part of premise parameters identification and in expanding MISO system into MIMO system. Using the proposed method, a fuzzy model of the drum boiler of the thermal power plant can be derived. In addition, feedwater control of the drum by fuzzy controller using the fuzzy model, is simulated.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.953-958
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• 1993

We develop a neural network control algorithm for the ACS (Advanced Control System). The ACS is an extended version of the DCS (Distributed Control System) to which functions of fault detection and diagnosis and advanced control algorithms are added such as neural networks, fuzzy logics, and so on. In spite of its usefulness proven by computer simulations, the neural network control algorithm, as far as we know, has no tool which makes it applicable to process control. It is necessary that the neural network controller should be turned into the function code for its application to the ACS. So we develop a general method to implement the neural network control systems for the ACS. By simulations using the simulator for the boiler of 'Seoul fire power plant unit 4', the methodology proposed in this paper is validated to have the applicability to process control.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.5
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• pp.385-393
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• 2013

In this paper, the mechanism identification and the avoidance measures on the phenomena of transient acoustic vibration amplified at the water-supply piping system to regulate the steam temperature of the boiler reheater in 500MW class supercritical power plant are presented. The pressure pulsation waves induced by the impeller passing of two feed-water pumps with five blades are coincident with the local acoustic modes of boiler reheater water-supply piping system. There are the phenomena amplified at the peaks of 5X, 10X, 15X and 20X in spectrums of piping vibration, sound pressure, and the feed-water's pressure pulsation waves. The shut-off device is installed in the piping system for the interception of pressure pulsation waves transmitted from two feed-water pumps and the modified design change of the piping layout is applied for the acoustic resonance avoidance. The acoustic natural frequencies are separated from the harmonics of pressure pulsation waves induced by the pump impellers passing through the design change of the span length. The acoustic vibration is gone by resonance avoidance measures. As a result, more than 20 dBA reduction is achieved from 100 dBA to 80 dBA.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.8
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• pp.906-915
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• 1988

The reliability enhancement is the critical issue in many computer applications, particulary in process control system. In this paper we describe how to achieve the reliability improvement in control system which is based on multiprocessors. The proposed method is accomplished by using the techniques of fault detection which composed by internal and external fault detections, fault isolation for removing the fault propagation, safety action for driving safe input, and fault diagnosis. This approach is experimented and asopted in boiler backup control system constructed by VMEbus system, CPU boards, graphic system, and other interface boards with UNIX operating system.

• Progress in Superconductivity and Cryogenics
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• v.15 no.1
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• pp.19-24
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• 2013

In this paper, the Superconductor flywheel energy storage system (SFESS) was used for the load frequency control (LFC) of an interconnected 2 area power system. The robust SFESS controller using quantitative feedback theory (QFT) was designed to improve control performance in spite of parameter uncertainty and unexpected disturbances. An overlapping decomposition method was applied to simplify SFESS controller design for the interconnected 2 area power system. The model for simulation of the interconnected 2 area power system included the reheat steam turbine, governor, boiler dynamics and nonlinearity such as governor deadband and generation rate constraint (GRC). To verify robust performance of proposed SFESS controller, dynamic simulation was performed under various disturbances and parameters variation of power system. The results showed that the proposed SFESS controller was more robust than the conventional method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2372-2377
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• 2003

Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,{\dot{x}},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.69.6-69
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• 2002

The optimal byproduct gas supply system was developed for the optimal management of the byproduct gases in the iron and steel making process based on EXCEL environment. It supplies optimal byproduct gas distribution result as well as analysis including expected electricity generation, holder level change, amount of oil consumption, energy distribution to each boiler, and efficiency of energy resource. To reflect the changing environment of the plant such as maintenance, the system was developed to easily change the optimization model for changing configuration of the system. To verify the performance of the system , case studies for various situation was performed with the developed system, a...