• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
• /
• pp.900-904
• /
• 1991

It is important and difficult to control the steam temperature in the once through boiler. Generally, steam temperature of once through boiler not only is controlled by boiler spray water flow, but also is influenced by feed water flow and fuel flow. So we have to make the same gain of fuel flow controller and feed water flow controller. This paper is shown the design and test of steam temperature and feed water flow control system for once through boiler in pusan thermal power plant.

• 전기학회논문지
• /
• 제59권9호
• /
• pp.1663-1672
• /
• 2010

The boiler feed-water pump controllers which can be applied to 500MW class coal fired power plants was developed. The validity of the developed controllers was shown via the applied test result in a power plant. It is expected that the developed controllers are used to retrofit the existing controllers that have surpassed their expected service life and have limited spare parts, and contributes to the stable operation of plants. Based on the collected data and analysis, new control schemes were developed and implemented during the overhaul period in the new control systems. During normal operation, feed water could be supplied to the boiler with the capability of the 1600t/h flow without any problems in automatic mode of controllers. In this study, the feed-water pump controllers were developed successfully. In addition, it is expected that the developed controllers can make the plant operation more stable and can be applied to a lot of power plants.

• 한국지능시스템학회논문지
• /
• 제13권3호
• /
• pp.322-327
• /
• 2003

가압경수로 원자력 발전소의 증기발생기 수위는 유량의 변동에 상반되는 수축(shrink)과 팽창(swell) 효과 등의 특성을 가지고 있으므로 제어가 어려운 대상으로 알려져 있다. 본 논문에서는 신경망을 이용하여 원자력발전소에서 사용되고 있는 두 개의 PI 제어기 중 부적절한 게인으로 조정된 제어기를 먼저 선택하고, 선택된 제어기의 게인을 퍼지 논리를 적용하여 조정하도록 구성하였다. 게인 조정을 위해 사용되는 기본 정보는 수위, 급수량, 그리고 증기량이다. 이 세 가지의 정보를 바탕으로 신경망을 통해 수위 제어기 또는 급수량 제어기 둘 중 하나의 제어기가 선택한 후 퍼지 자기동조기(self-tuner)를 이용하여 PI 제어기의 게인을 알맞게 조정하게 된다. 퍼지 자기동조기의 규칙은 증기발생기의 상태를 표현하는 입ㆍ출력 데이터의 특성으로부터 추출하였다. 이상의 두 과정을 통해 적절한 제어기를 선택하고, 선택된 제어기의 게인을 알맞게 조정하는 것이 본 논문의 목적이다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
• /
• pp.553-556
• /
• 1989

Nowadays in power plant feed water control, it is very important to retain the stable drum level though power changes very fast. For the stable drum level in power plant, we have to model our plants and get the system functions. We make the L.Q. controller by using these functions and apply it to these systems. And we get the more stable drum level which is controlled by feed water qualities.

• 제어로봇시스템학회논문지
• /
• 제4권3호
• /
• pp.321-328
• /
• 1998

When we control the level of the steam generator in the nuclear power plants, a swell and shrink arises from many disturbances such as feed water rate, feed water temperature, main steam flow rate, and coolant temperature. If we use the conventional type of PI controller in this system, we will not have stability during controlling at lower power, the removal function of disturbances, and a load follow-up control effectively. In this paper, we study the application of a 2-Degree of Freedom(2-DOF) PID controller to the level control of the steam. generator of nuclear power plants through the simulation and the experimental steam generator. We use the parameters $\alpha$, $\beta$, $\gamma$ of the 2-DOF PID controller for the removal of disturbances and the parameters Kp,Ti,Td of the conventional type of PID controller for controlling setpoint. The back-propagation learning algorithm of neural network is used for tuning the 2-DOF PID controller. We can find satisfactory results of the removal of the disturbances and the tracking function in the change of setpoint through the simulation and experimental steam generator.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.65.2-65
• /
• 2001

There are not only lots of controllers such as UMC(Unit Master Controller), BMC(Boiler Master Controller), Fuel Flow controller, Air flow controller, Feed water flow controller, S/H R/H Temperature controller and so on, but also compensation controller such as BTU compensator, Fuel/Water ratio controller and O2 Co controller to take automatic control in the super critical once through boiler. It is important to make complete automation of boiler to use the compensation controller like BTU compensator. For example, In case of some boiler condition, operator has to change combustion parameter for changing the coal, on the contrary BTU compensator can calculate set value of the fuel flow and reset the fuel flow demand by itself. This paper shows us the logic and instruction regarding compensation controller of boiler that can be operated automatically.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제18권1호
• /
• pp.46-63
• /
• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• 대한전기학회논문지
• /
• 제39권12호
• /
• pp.1281-1287
• /
• 1990

A new thermal power plant feed-water system model, which is based on Astrom, is presented. Astrom's model has some difficulties in applying to practical systems because it is not able to measure the heat and energy transfer loss. Hence, in order to make up for these difficulties, the Gas State Equation is added to the model. Computer simulations are performed to show the validity of the new model at thermal power plant with practical boiler operating data and to verify the L.Q. controller effect on boiler drum level system.

• Nuclear Engineering and Technology
• /
• 제44권4호
• /
• pp.363-368
• /
• 2012

A feedwater controller targeted for an ABWR has been implemented using a modern field programmable gate array (FPGA), and verified using the full scope simulator at Taipower's Lungmen nuclear power station. The adopted control algorithm is a rule-based fuzzy logic. Point to point validation of the FPGA circuit board has been executed using a digital pattern generator. The simulation model of the simulator was employed for verification and validation of the controller design under various plant initial conditions. The transient response and the steady state tracking ability were evaluated and showed satisfactory results. The present work has demonstrated that the FPGA based approach incorporated with a rule-based fuzzy logic control algorithm is a flexible yet feasible approach for feedwater controller design in nuclear power plant applications.

• Journal of Electrical Engineering and Technology
• /
• 제11권2호
• /
• pp.265-273
• /
• 2016

A water wall system is one of the most important components of a boiler in a thermal power plant, and it is a nonlinear Multi-Input and Multi-Output (MIMO) system, with 6 inputs and 3 outputs. Three models are developed and comp for the controller design, including a linear model, a multilayer feed-forward neural network (MFNN) model and an Echo State Network (ESN) model. First, the linear model is developed by linearizing a given nonlinear model and is analyzed as a function of the operating point. Second, the MFNN and the ESN are developed by using training data from the nonlinear model. The three models are validated using Matlab with nonlinear input-output data that was not used during training.