• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.2
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• pp.94-99
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• 2004

In this paper, We design a RF control system capable of handling multiple POS thermal printers. The system has three parts including embedded master controller, RF controller and high-speed thermal printer. Specially the designed linux embedded controller has simple structure and high performance to connect the TCP/IP network. The effectiveness of the developed RF control system is shown by proposed food ordering system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.84-89
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• 2003

Fuzzy controller is one of the succeed controller used in the process control in case of model uncertainties. But it my be difficult to fuzzy controller to articulate the accumulated knowledge to encompass all circumstance. Hence, it is essential to provide a tuning capability. There are many parameters in fuzzy controller can be adapted, scale factor tuning of normalized fuzzy controller is one of the adaptation parameter. Two adaptation methods are implemented in this work on an experimental thermal process, which simulate heating process in liquefied petroleum gases (LPG) recovery process in one of petrochemical industries: Gradient decent (GD) adaptation method; supervisory fuzzy controller. A comparison between the two methods is discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1211-1217
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• 2001

This paper presnts a controller for the heat capacity of thermal storage systems using off-peak electricity which is composed of an identifier using neural networks and a storage time adjuster in order to store exactly the required thermal energy without loss. Since thermal storage systems have nonlinear characteristics and large time constant, even if we predict the heating load accurately, it is very difficult to store exactly the required thermal energy. Thus, in the neural network for the identifier, the adaptive learning rate for high learning speed and bit inputs based on state changes of thermal storage power source are used. Also a hardware for the controller using a microprocessor is developed. The performance of the proposed controller is shown by experiment.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.5
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• pp.52-59
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• 2008

The accuracy of the machine tools is degraded because of thermal error of structure due to thermal variation. To improve the accuracy of a machine tools, measurement and prediction of thermal error is very important. The main part of thermal source is spindle due to high speed with friction. The thermal error of spindle is very important because it is over 10% in total thermals errors. In this paper, the suitable thermal error prediction technology for machine tools with open architecture controller is developed and implemented to machine tools. Two thermal error prediction technologies, neural network and multi-linear regression, are investigated in several methods. The multi-linear regression method is more effective for implementation to CNC. The developed thermal error prediction technology is implemented on the internal function of CNC.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2001.05a
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• pp.238-242
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• 2001

In this paper, we proposed an optimal identification method of the membership functions and the numbers of fuzzy rule base for the stabilization controller of the Thermal process control system by RVEGA. Although fuzzy logic controllers and expert systems have been successfully applied in many complex industrial process, they must rely on experts knowledges. So it is difficult in determination of the linguistic state space, definition of the membership functions of each linguistic term and the derivation of the control rules. To verify the validity of this RVEGA-based fuzzy controller, Thermal process control system, with strong nonlinear dynamics, was selected for application of this algorithm and compare with PI controller, and the empirically improved fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1088-1092
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• 2003

This paper presents a combined lookup table technique and PI-type controller. The purpose of the designed controller is applied to control the nonlinear system as thermal process. The proposed controller is easy and convenient to design based on a commercial controller. The performances of the proposed controller were studied using the thermal plant model under temperature control. The experimental results included demonstrate the good performance of the proposed controller.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2584-2586
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• 2000

A drum level control is one of the most important control systems in thermal power plant. The control objective of drum level of boiler in thermal power plant is to maintain drum level at constant set-point regardless of disturbance such as main steam flow. The implemented drum level controller is the cascade PI controller. The important factor in drum level controller is the parameters of two PI controllers. The tuning of PI controller parameter is tedious and time-consuming job. In this paper, the relay feedback Ziegler - Nichols tuning method extended to auto-tune cascade PI drum level controller. Finally, the simulation result using boiler model in Power Plant shows the validity of auto-tuned cascade PI controller.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.213-215
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• 1987

As a means of improving the reliability of the analog type controller for the thermal power plant, an efficient method is proposed, which is to place the hardware redundancy, i.e. a back-up controller with fault detecting capability. FTCS is implemented by using multi-processors and it is experimentally verified that the back-up controller takes over the role of the original controller, controlling the faulty loop.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1455-1459
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• 2003

This paper presents an n-steps on-off controller to maintain the desired temperature of the thermal process. The proposed technique is simple and convenient to implement based on the programmable commercial controller. The thermal plant model is experimented to observe the performances of the proposed controller. The experimental results included demonstrate the good performance of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.788-791
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• 1996

A mathematical model is developed for thermal solution copolymerization of styrene and acrylonitrile in a continuous stirred tank reactor(CSTR). Computational studies are carried out with the continuous copolymerization system model developed in this work to give the monomer conversion, copolymer composition and the average molecular weights of the copolymer. By performing the dynamic analysis of the reaction system, the polymer properties against the changes in the operating conditions are determined quantitatively. The cascade PID and fuzzy controller show satisfactory performances for both set point tracking and disturbance rejection. Especially, the fuzzy controller is superior to the PID controller.