• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.2
• /
• pp.102-110
• /
• 1999

The aim of this paper is to suggest a design method of the optimal model following control system using gerelic algoritlun (GA). This control system is designed by applying GA with reference model to the optimal determinination of weighting matrices Q, R that are given by LQ regulator prooblem. The method to do this is that all the diagooal elements of weighting matrices are optimized simultaneously by GA, in the search domain selected adequately. And, we design the mxiel following control system to boiler-turbine equipment by the proposed mothod. The model following control system designed by this mothod has the better command tracking perfannaoce than that of the control system designed by the trial-and-error method. The effectiveness of this cootrol System is verified by computer simulation.

• Journal of Advanced Marine Engineering and Technology
• /
• v.36 no.1
• /
• pp.126-132
• /
• 2012

This paper suggests a design method of the model-following H${\infty}$ control system having robust performance. This H${\infty}$ control system is designed by applying genetic algorithm(GA) with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design H${\infty}$ controller in the state space. These weighting functions and design parameter ${\gamma}$ are optimized simultaneously in the search domain guaranteeing the robust performance of closed-loop system. The effectiveness of this H${\infty}$ control system is verified by applying to the boiler-turbine control system.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.350-350
• /
• 2000

Since the heat exchange system, such as the boiler of power plant, gas turbine, and radiator require a high rate heat efficiency and the efficiency of these systems is depended on the control methods. However, it is important f3r operator to understand control system of these systems. In order to properly apply control equipment to these process control systems, such as boiler, any other heat process, or process control system it is necessary to understand the basic aspects and operation principle of the process that relate control, interrelationships of the process characteristics, and the dynamics that are involved. Generally, PID controllers are used in these systems but it is difficult for engineer to understand the complex dynamics and the tuning method because of the coupling action and disturbance in the system loop. In this paper, we design an effective experimental system fur automatic control education and analyze its characteristics through experimental system and industrial plant control software to study how they can team automatic control system by experiments.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2342-2344
• /
• 2000

Many years ago, most of thermal power plants built in this country were of subcritical pressure, of medium or small size, of constant pressure operation, of drum type steam generator. But, nowadays, almost all of them were of high efficiency, of supercritical pressure, of great capacity(about 500MW), of sliding pressure operation, of once through type steam generator. Presently built once through boiler introduces turbine bypass systems to variable pressure operation which eliminates unexpected materials in boiler tube during startup, minimizes fuel loss by short startup period, eventually improves total efficiency and power system stability

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1664_1665
• /
• 2009

Many years ago, most of thermal power plants built in this country were of subcritical pressure, of medium or small size, of constant pressure operations and of drum type steam generators with circulation type boilers. But, nowadays almost all of them were of high efficiency, of supercritical pressure, of big capacity, of sliding pressure operations, and of once through type steam generator. It has such advantage as the reduction of startup duration, but it control system and operation method are very complicated. It has a big difference in operation method of turbine and boiler. The feedforward control needs to be introduced to prevent such problems as thermal shock during the transit from normal operation into bypass operation. This paper introduces the turbine control and turbine bypass control during startup of thermal power plants.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1804-1805
• /
• 2011

In recent year there has been an increasing interest in the dynamic simulation of complex systems. This study uses a large-scale forty-seventh order fossil fuel power plant. Twenty-three state variables are associated with the physical processes and twenty-four state variables associated with the control system. The plant model is expected to predict all dominant effects in a steady and transient state. In this study, the power plant model is reorganized into four subsystems, each with its controller, and the four connected to each other through a manager, which is a fifth part to the system. The four parts of the unit are the boiler system, steam turbine system, condenser system, and feedwater system.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2455-2457
• /
• 2000

In this paper, it is proposed a neural adaptve control algorithm for boiler-turbine system. Control inputs are constructed using RBF Neural networks and variable structure inputs are added to improve the robustness. This proposed algorithm does not need the information about parameters and can assure the robustness under the output disturbance and parameter perturbations. The results of computer simulations is presented to verify the efficiency of the proposed algorithm.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.2
• /
• pp.234-234
• /
• 1999

The aim of this paper is to suggest a design method of the optimal model following control system using genetic algorithm (GA). This control system is designed by applying GA with reference model to the optimal determination of weighting matrices Q, R that are given by LQ regulator problem. The method to do this is that all the diagonal elements of weighting matrices are optimized simultaneously by GA, in the search domain selected adequately. And we design the model following control system to boi1er-turbine equipment by the proposed method. The model following control system designed by this method has the better command tracking performance than that of the control system designed by the trial-and-error method. The effectiveness of this control system is verified by computer simulation.

• Proceedings of the KIEE Conference
• /
• 2001.11b
• /
• pp.282-285
• /
• 2001

In general, the PSS/E program based on RMS mathematical models is used for analyzing the steady state and transient stability phenomena of full-scale large power system. Whereas, the EMTDC program unlike PSS/E, studies the specific reduced small-scale power systems as a basis of instantaneous value mathematical models and used to analyze the Electro-Magnetic transient characteristics. The PSS/E provides various control models such as exciter, governor, PSS models and TGOV5 model but there are few control models in EMTDC. In this paper, we developed EMTDC model for TGOV5 of a steam turbine and boiler which represents governor action, main, reheat and low-pressure effects, including boiler effects. The EMTDC model is developed by examining PSS/E control block and using User Define Model(UDM) in addition to default.lib provided by EMTDC. We verify the correctness of developed TGOV5 model with PSS/E and EMTDC simulation results using Governor Step(GSTEP) method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.24 no.1
• /
• pp.91-97
• /
• 2010

In this paper, we present simulation results of Dynamic Matrix Control (DMC) to a Once-through boiler steam temperature. In order to control the steam temperatures, we choose spray and damper as two input variables. Then, the step response model is generated for the two major output variables by step test. After that, on-line optimization is performed using $(2\times2)$ step response model. Proposed controller is applied to the APESS (Doosan company's boiler model simulator) and the simulation results show satisfactory performance of proposed control.