• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.43-49
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• 1998

This paper describes a phase-shift pulse-width modulation and pulse-frequency modulation seriesresonant high-frequency inverter using IGBT for the power control of high-frequency inductionheating using fuzzy, which is practically applied for 2 0- 5~0 0~~ ~in 1d uction-heating and meltingpov~er supply in industrial fields. The adaptive frequency tracking based phase-shifting PWMregillation scheme is presented in order to minimize switching losses. The trially-producedbreadboards using IGBT are succesfully demostrated and discussed.discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.207-210
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• 1997

In this paper, a hierarchical fuzzy controller for stabilization of the inverted pendulum system is proposed. The facility of this hierarchical fuzzy controller which has a swing-up control mode and a stabilization one, moves a pendulum in an initial natural stable equilibrium point and a cart in arbitrary position to an unstable equilibrium point and a center of rail. Specially, the virtual equilibrium point (.PHI.$_{VEq}$ ) which describes functionally considers the interactive dynamics between a position of cart and a angle of inverted pendulum is introduced. And comparing with the convention optimal controller, the proposed hierarchical fuzzy inference made substantially the inverted pendulum system robust and stable.e.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.407-414
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• 2001

In this paper, we present a decentralized robust adaptive fuzzy controller for the transient stability and voltage regulation of a multimachine power system under a sudden fault. Power systems have uncertain dynamics due to various effects such a lightning, severe storms and equipment failure in addition to interconnections between generators. Hence a robust controller to deal with these uncertainties in needed. The fuzzy systems are adapted using a Lyapunov-based design and the stability of each closed-loop system is guaranteed. Simulation results show that satisfactory performance is achieved by proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.297-305
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• 1996

In this paper a novel robust adaptive fuzzy controller for the nonlinear system with state-dependent uncertainty is proposed. The conventional adaptive fuzzy controller determines the function of state variable bounding the state-dependent uncertain term in the system dynamics on the local state space by off-line calculation. Whereas the proposed method determines that function by the fuzzy inference so that it guarantees the stability of the closed loop system globally on the whole state space. In addition, the method is applicable to the multi-input system. We applied the proposed method to the Burn Control of the Tokamak fusion reactor whose dynamics contains the state-dependent uncertainty and proved the effectiveness of the scheme by using the simulation results.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.112-120
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• 2001

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing the approach of an adaptive dual fuzzy logic. Some goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a high building, when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of a fuzzy rule base. Controls for co-operation among elevators in a group control algorithm arte essential, and the most critical control function in the group controller is an effective and proper hall call assignment of elevators. The group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.710-717
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• 1993

In this paper, we focus upon the design and applications of adaptive fuzzy-neuro controllers. An intelligent control system is proposed by exploiting the merits of two paradigms, a fuzzy logic controller and a neural network, assuming that we can modify in real time the consequential parts of the rulebase with adaptive learning, and that initial fuzzy control rules are established in a temporarily stable region. We choose the structure of fuzzy hypercubes for the fuzzy controller, and utilize the Perceptron learning rule in order to update the fuzzy control rules on-line with the output error. And, the effectiveness and the robustness of this intelligent controller are shown with application of the proposed adaptive fuzzy-neuro controller to control of the cart-pole system.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.382-386
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• 1992

In this paper, the author proposed FLVSC(Fuzzy Logic Variable Structure Controller), of which control rules are extracted from the concepts of VSC(Variable Structure Control). FLC(Fuzzy Logic Controller) based on linguistic rules has the advantages of not needing of some exact mathematical model for plant to be controlled. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbances, parameter variations and uncertainties in sliding mode. In addition, the method has the properties of FLC - noise rejection capability etc. The computer simulations have been carried out for a DC servo motor to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.173-179
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• 2000

While a cutting tool is machining a workpiece at various cutting depth, the feedrate is usually selected based on the maximum depth of cut. Even if this selection can avoid power saturation or tool breakage, it is very conservative compared to the capacity of the machine tools and can reduce the productivity significantly. Many adaptive control techniques that can adjust the feedrate to maintain the constant cutting force have been reported. However, these controllers are not very widely used in manufacturing industry because of the limitations in measuring the cutting force signals. In this paper, turning force control systems based on the estimated cutting force signals are proposed. A synthesized cutting force monitor is introduced to estimate the cutting force as accurately as a dynamometer does. Three control strategies of PI, adaptive and fuzzy logic controllers are applied to investigate the feasibility of utilizing the estimated cutting force fur turning force control. The experimental results demonstrate that the proposed systems can be easily realized in CNC lathe with requiring little additional hardware.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.3
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• pp.224-232
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• 2006

The paper proposes the artificial neural network(ANN) sensorless control of induction motor drive with adaptive fuzzy logic controller(AFLC). Also, this paper proposes the speed control of induction motor using AFC and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The proposed control algorithm is applied to induction motor drive system controlled AFLC and him controller. And this paper is proposed the results to verify the effectiveness of the AFLC and ANN controller.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.3
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• pp.108-114
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• 2015

Ballast water is carried by ships to ensure stability, trim and structural integrity. When a ship loads cargo, the ballast water is discharged. When foreign marine microorganisms are introduced into new marine environments, they pose a threat to the local marine ecological system. UV system is commonly used for the disinfection of waste and surface water. This method would not be as efficient because some species do survive to form viable populations, much of the sediment and organisms at the bottom of tanks, and may become serious pests. In this paper, we designed and implemented ballast water treatment system using fuzzy PID controller to prevent lamp damage, and to reduce the formation of the viable populations. The experiments were conducted with ballast water treatment system using fuzzy PID controller with short time exposure to the temperature above $40^{\circ}C$. This system was shown to be effective by significantly reducing bacterial population and lamp life extension through appropriate temperature of ballast water.