• Journal of Biosystems Engineering
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• v.15 no.2
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• pp.134-142
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• 1990

This study was carried out for the development of greenhouse temperature control system by modifying an APPLE-II microcomputer attached with several interface systems. The interface systems are composed of 12 bit A/D converter, output port, multiplexer, time clock, etc. Under the operation of developed system, the greenhouse temperature was to be manipulated within the setting temperatures assumed to be appropriate for certain plant growth. The temperature control equimpents installed in the greenhouse are one-speed propeller type fan and two-phase electric heater, which are selectively started or stopped according to the control logic programmed in the control system. The results are summarized as follows : 1. The difference between two temperatures measured by the developed system and the self-recording thermometer calibrated with standard thermometer was less than $1^{\circ}C$. 2. When the temperature were measurd by 12 bit A/D converter and both electric heater and ventilation fan were controlled by developed ON/OFF logic, greenhouse temperature showed narrow fluctuation bands of less than $1^{\circ}C$ near the setting temperatures. 3. The temperature acquisition and control system developed in this study is expected to be applicable to environment control system such as greenhouse only by modifying the logic based on long term experimental data. 4. In order to reduce the measurement error and to increase the system control efficiency, it is recommended that continuous study should be carried out in the aspect of eliminating various systematic noises and improving the environmental control logic.

• Journal of IKEEE
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• v.19 no.4
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• pp.479-485
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• 2015

A resistance deviation-to-time interval converter based on dual-slope integration using second generation current conveyors (CCIIs) is designed for connecting resistive bridge sensors with a digital system. It consists of a differential integrator using CCIIs, a voltage comparator, and a digital control logic for controlling four analog switches. Experimental results exhibit that a conversion sensitivity amounts to $15.56{\mu}s/{\Omega}$ over the resistance deviation range of $0-200{\Omega}$ and its linearity error is less than ${\pm}0.02%$. Its temperature stability is less than $220ppm/^{\circ}C$ in the temperature range of $-25-85^{\circ}C$. Power dissipation of the converter is 60.2 mW.

• Journal of the Semiconductor & Display Technology
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• v.11 no.2
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• pp.63-69
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• 2012

As decreasing size of chips, the need of wafer level packaging is increased in semi-conductor and display industries. Temperature uniformity is a crucial factor in vacuum soldering process to guarantee quality of bonding between chips and wafer. In this paper, a stepwise iterative algorithm has been suggested to obtain output profile of each heat source. Since this algorithm is based on open-loop stepwise iterative experimental technique, it is easier to implement and cost effective than real time feedback controls. Along with some experiments, it was shown that the suggested algorithm can remarkably improve temperature uniformity of wafer during whole heating process compared with the ordinary manual trial-and error method.

• Journal of the Microelectronics and Packaging Society
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• v.8 no.4
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• pp.53-57
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• 2001

A short shot is an incomplete molded part caused by insufficient material injection into the mold. Remedial actions to control the process conditions can be taken by injection molding experts based on their knowledge and experiences. However, it is very difficult for non-experts to avoid short shot by finding the proper process conditions such as mold temperature, melt temperature and filling time. In this paper, an intelligent generator of optimal process conditions based upon fully logic algorithm is proposed so that trial and error can be minimized and non-experts an well at experts can also find the optimal process conditions.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.543-545
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• 2019

Recently, the demand for smart farms is increasing due to the increase in the cultivation area such as horticulture, fruit trees and special crops. However, due to the irregular weather changes and the cultivation method of the crops due to the different cultivation environment, there are frequent occurrence of diseases and insect pests and infectious diseases due to system error or carelessness, and the cycle is also very short. In addition, the Smart Farm business has been built by combining various sensors (temperature, humidity, CO2, illumination) and LED lighting, but it is costly in terms of frequent errors, lack of power supply, And thus the management can not be efficiently managed. Therefore, this paper combines real time sensing technology based on IoT Platform and high performance control technology to control pests and equipment errors and monitor the growth status of crops in real time based on big data analysis and Artificial Intelligence System.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.33-37
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• 2002

A short shot is a molded part that is incomplete because insufficient material was injected into the mold. Remedial actions to control the process conditions can be taken by the injection molding experts based on their knowledge and experience. However, it is very difficult for the non-experts to avoid short shot by finding the proper process conditions such as mold temperature, melt temperature and filling time. In this paper, an intelligent generator of the optimal process conditions based upon fuzzy logic algorithm is proposed so that trial and error can be minimized and the non-experts as well as the experts can also find the optimal process conditions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.402-405
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• 2001

A short shot is a molded part that is incomplete because insufficient material was injected into the mold. Remedial actions to control the process conditions can be taken by the injection molding experts based on their knowledge and experience. However, it is very difficult for the non-experts to avoid short shot by finding the proper process conditions such as mold temperature, melt temperature and filling time. In this paper, an intelligent generator of the optimal process conditions based upon fuzzy logic algorithm is proposed so that trial and error can be minimized and the non-experts as well as the experts can also find the optimal process conditions.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.687-690
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• 2003

This paper presents the development of Programmable Logic Controller (PLC) and network to design the redundant control system in order to control the high priority process. The industrial process that cannot be shutdown or the effect of the shutting down takes abundantly damage. In this article, we say that the high priority process. The redundant systems are designed for controlling the high priority process that the control system must have many controllers to instead the main controller when it has some error. This paper we designed the redundancy control system by the advantage of the high-speed communication on the PLC’s network. The temperature control system and the traffic light control system used as the case study. Each example processes consist of two sets of controller. Our scheme we can increase the reliability prevents process down time and reduces the cost of opportunity to loss also.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.78-86
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• 2003

Multivariable control 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, Pill 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 Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

• KIEE International Transaction on Systems and Control
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• v.2D no.2
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• pp.78-91
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• 2002

In the thermal power plant, there are six manipulated variables: main steam flow, feedwater flow, fuel flow, air flow, spray flow, and gas recirculation flow. There are five controlled variables: generator output, main steam pressure, main steam temperature, exhaust gas density, and reheater steam temperature. Therefore, the thermal power plant control system is a multinput and output system. In the control system, the main steam temperature is typically regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. However, strict control of the steam temperature must be maintained to avoid thermal stress. Maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature versus changes in fuel flow rate, difficulty of control of the main steam temperature control and the reheater steam temperature control system owing to the dynamic response characteristics of changes in steam temperature and the reheater steam temperature, and the fluctuation of inner fluid water and steam flow rates during the load-following operation. Up to the present time, the Proportional-Integral-Derivative Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on the characteristic comparison of the PID controller and the modified 2-DOF PID Controller (Two-Degrees-Freedom Proportional-Integral-Derivative) on the DCS (Distributed Control System). The method is to design an optimal controller that can be operated on the thermal generating plant in Seoul, Korea. The modified 2-DOF PID controller is designed to enable parameters to fit into the thermal plant during disturbances. To attain an optimal control method, transfer function and operating data from start-up, running, and stop procedures of the thermal plant have been acquired. Through this research, the stable range of a 2-DOF parameter for only this system could be found for the start-up procedure and this parameter could be used for the tuning problem. Also, this paper addressed whether an intelligent tuning method based on immune network algorithms can be used effectively in tuning these controllers.