• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.601-604
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• 1996

It is well known that steam generator water level control at low power operation has many difficulties in a PWR (pressurized water reactor) nuclear power plant. The reverse process responses known as shrink and swell effects make it difficult to control the steam generator water level at low power. A new automatic control logic to remove the reverse process responses is proposed in this paper. It is implemented in PLC (programmable logic controller) and evaluated by using test equipment in Korea Atomic Energy Research Institute. The simulation test shows that the performance requirements is met at low power (below 15%). The water level control by new control logic is stabilized within 1% fluctuation from setpoint, while the water level by YGN 3 and 4 control logic is unstable with the periodic fluctuation of 25% magnitude at 5% power.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.490-493
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• 1996

This paper presents a control scheme for the motion of a 2 DOF robot manipulator. Robot manipulators are multivariable nonlinear systems. Fuzzy logic is avaliable human-like control without complex mathematical operation and is suitable to nonlinear system control. In this paper, Implementation of fuzzy logic control of robotic manipulators shows. Algorithm has been performed with simulation packages MATRIXx and SystemBuild.

• Nuclear Engineering and Technology
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• v.42 no.3
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• pp.329-338
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• 2010

We developed an achievable control logic for the reactor power level during a power maneuvering event and set up some constraints for the control of the reactor power in a conceptual sodium-cooled fast reactor (KALIMER-600) that was developed at KAERI. For simulating the dynamic behaviors of the plant, we developed a fast-running performance analysis code. Through various simulations of the power maneuvering event, we evaluated some suggested control logic for the reactor power and found an achievable control logic. The objective of the control logic is to search for the position of the control rods that would keep the average temperature of the primary pool constant and, concurrently, minimize the power deviation between the reactor and the BOP cycle during the power maneuvering. In addition, the flow rates of the primary pool and the intermediate loop should be changed according to the power level in order to not violate the constraints set up in this study. Also, we evaluated some movement speeds of the control rods and found that a fast movement of the control rods might cause the power to fluctuate during the power maneuvering event. We suggested a reasonable movement speed of the control rods for the developed control logic.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.133.2-133
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• 2001

This paper focuses on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several independent, but interacting processes running on two separate stations. By using this NCS, the network delay is analyzed to find the cause of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controllers performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice for NCS due to its robustness against parameter uncertainty.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.5
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• pp.196-206
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• 2000

These days, the fuzzy logic or the fuzzy set theory has received attention from a number of researchers in the area of industrial application. Moreover, the fuzzy logic control has been successfully applied to a large numbers of control problems where the conventional control methods had failed. Using this control theory we designed a climate controller for an automotive climate control system whose mathematical model is difficult. This paper describes an automotive climate control where the fuzzy control has been used to stabilize parameter uncertainties and disturbance effects. To show the validity and effectiveness of the proposed control method, the fuzzy logic controller was implemented with a philips 80C552 microcomputer chip and tested in an actual vehicle. From the experimental results, it could be conduced that the proposed controller is superior to conventional controllers in both control performance and thermal comfort. The climate control system in cars is difficult to model mathematically so we tested a fuzzy logic control system which promised better results.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.834-841
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• 2006

Recently, many enterprises are installing AMSs(Automated Manufacturing Systems) for their competitive advantages. As the level of automation increases, proper design and validation of control logic is a imperative task for the successful operation of AMSs. However, current discrete event simulation methods mainly focus on the performance evaluation. As a result, they lack the modeling capabilities for the detail logic of automated manufacturing system controller. Proposed in this paper is a method of validation of the controller logic for automated material handling system using an object-oriented design and simulation. Using this method, FA engineers can validate the controller logic easily in earlier stage of system design, so they can reduce the time for correcting the logic errors and enhance the productivity of control program development Generated simulation model can also be used as a communication tool among FA engineers who have different experiences and disciplines.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.640-643
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• 1997

This paper describes speed controller of a induction motor for electric vehicles using PLL and Fuzzy logic. The proposed system is combined precise speed control of PLL and robust, fast speed control of Fuzzy logic. The motor speed is adaptively incremented or decremented toward the PLL locking range by the Fuzzy logic using information of sampled speed errors and then is maintained accurately by PLL. The results of experiment show excellence of proposed system and that the proposed system is appropriates to control the speed of induction motor for electric vehicles.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.28-31
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• 1997

This paper describes the quick and precise controlling method for home-applied refrigerator. The proposed controller is based on the fuzzy logic control method and is designed for better performance in maintaining the constant temperature of the refrigerator. The temperature of the refrigerator is controlled by the cooling air blowing fan motor which is put on, off according to fuzzy logic controller. Finally, I study the performance of the proposed controller through the computer simulation about the approximated model of the refrigerator.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.281-287
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• 2002

This paper investigates on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several inde-pendent, but interacting processes running on two separate stations. By using this NCS, the network-induced delay is analyzed to find the cause and effect of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controller's performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice far NCS due to its robustness against parameter uncertainty.