• Journal of Information Management
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• v.24 no.3
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• pp.73-100
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• 1993

In attempting to respond to boolean retrieval system's limitations, this paper presents the design of a retrieval system using fuzzy logic. The fuzzy retrieval system introduces the weights of terms in the documents and in the query and makes use of them to determine how much relevant a document is to the given query. After comparing and analyzing the previous researches, an effective model of the fuzzy retrieval system is suggested and the performance of the system is evaluated through actual examples.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1978-1987
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• 2014

Power requirement to the induction heating system varies during the heating process. A closed loop control is required to have a smooth control over the power. In this work, a constant frequency pulse density modulation based power tracking control scheme for domestic induction heating system is developed using the Fuzzy Logic Controller. In the conventional power modulation schemes, the switching losses increase with the change in the load. The proposed pulse density modulation scheme maintains minimum switching losses for the entire load range. This scheme is implemented for the class-D series resonant inverter system. Fuzzy logic controller based power tracking control scheme is developed for domestic induction heating power supply for various power settings. The open loop and closed loop simulation studies are done using the MATLAB/Simulink simulation tool. The control logic is implemented in hardware using the PIC16F877A microcontroller. Fuzzy controller tracks the set power by changing the pulse density of the gate pulses applied to the inverter. The results obtained are used to know the effectiveness of the fuzzy logic controller to achieve the set power.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.3
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• pp.295-300
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• 2018

Conventionally, a PI control algorithm has been widely used as a speed control algorithm for BLDC motor. The PI control algorithm has a disadvantage in that is slow to reach the steady state due to the slow speed and torque response with various speed changes. Therefore, in this paper, PWM fuzzy logic control algorithm which can reach the steady state quickly by improving the response speed although there is a little overshoot is proposed. PWM reduces response speed and fuzzy logic control algorithm minimizes overshoot. The proposed PWM fuzzy logic control algorithm consists of DC chopper, PWM duty cycle regulator, and fuzzy logic controller. The performance and validity of the proposed algorithm is verified by simulation with Simulink of Matlab 2018a.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.826-829
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• 1993

Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unknown deadzones. We propose a novel two-layered fuzzy logic controller for controlling systems with deadzones. The two-layered control structure consists of a fuzzy logic-based pre-compensator followed by a conventional fuzzy logic controller. Our proposed controller exhibits superior transient and steady-state performance compared to conventional fuzzy controllers. We illustrate the effectiveness of our scheme using computer simulation examples.

• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.127-129
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• 2008

This paper describes a method of approximate reasoning for fuzzy control of servo system, based on decomposition of -level fuzzy sets. It is propose that logic circuits for fuzzy PI+PD are a body from fuzzy inference to defuzzificaion in cases where the output variable u directly is generated PWM. The effectiveness for robust and faster response of the fuzzy control scheme is verified for a variable parameter by comparison with a PID control and fuzzy control. A position control of DC servo system with a fuzzy logic controller successfully demonstrated.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.337-352
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• 2005

In this paper, a fuzzy logic implementation of the random early detection (RED) mechanism [1] is presented. The main objective of the proposed fuzzy controller is to reduce the loss probability of the RED mechanism without any change in channel utilization. Based on previous studies, it is clear that the performance of RED algorithm is extremely related to the traffic load as well as to its parameters setting. Using fuzzy logic capabilities, we try to dynamically tune the loss probability of the RED gateway. To achieve this goal, a two-input-single-output fuzzy controller is used. To achieve a low packet loss probability, the proposed fuzzy controller is responsible to control the $max_{p}$ parameter of the RED gateway. The inputs of the proposed fuzzy controller are 1) the difference between average queue size and a target point, and 2) the difference between the estimated value of incoming data rate and the target link capacity. To evaluate the performance of the proposed fuzzy mechanism, several trials with file transfer protocol (FTP) and burst traffic were performed. In this study, the ns-2 simulator [2] has been used to generate the experimental data. All simulation results indicate that the proposed fuzzy mechanism out performs remarkably both the traditional RED and Adaptive RED (ARED) mechanisms [3]-[5].

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.6
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• pp.625-632
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• 1992

This paper presents a new dc-motor position control approached by Variable Structure System. In order to eliminate a steady-state position error, we propose a switching function composed of position error, velocity, and current ripple. The switching function has an advantage compared to other ones. To determine the control signal voltage, we use a fuzzy logic method. The simulation results show expected performances.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.48-57
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• 1997

This paper presents the automatic construction and parameter optimization technique for fuzzy logic controllers using genetic algorithm. In general. the design of fuzzy logic controllers has difficulties in the acq~lisition of expert's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controllers c:an be degraded in the case of plant parameter variations or unpredictable incident which a designer may have ignored, and the parameters of fuzzy logic controllers obtained by expert's control action may not be optirnal. Some of these problems can be resolved by the use of genetic algorithm. The proposed method can tune the parameters of fuzzy logic controllers including scaling factors and determine: the appropriate number of fuzzy rulcs systematically. Finally, we provides the second order dead time plant to evaluate the feasibility and generality of the proposed method. Comparison shows that the proposed method can produce fuzzy logic controllers with higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controllers.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.11-14
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• 2003

In this paper, we use Fuzzy Logic and Potential field method for optimal path planning of an autonomous mobile robot and apply to navigation for real-time mobile robot in 2D dynamic environment. For safe navigation of the robot, we use both Global and Local path planning. Global path planning is computed off-line using sell-decomposition and Dijkstra algorithm and Local path planning is computed on-line with sensor information using potential field method and Fuzzy Logic. We can get gravitation between two feature points and repulsive force between obstacle and robot through potential field. It is described as a summation of the result of repulsive force between obstacle and robot which is considered as an input through Fuzzy Logic and gravitation to a feature point. With this force, the robot fan get to desired target point safely and fast avoiding obstacles. We Implemented the proposed algorithm with Pioneer-DXE robot in this paper.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.5-9
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• 2005

One of the imminent problems to be solved within wireless sensor network is to balance out energy dissipation among deployed sensor nodes. In this paper, we present a transmission relay method of communications between BS (Base Station) and CHs (Cluster Heads) for balancing the energy consumption and extending the average lifetime of sensor nodes by the fuzzy logic application. The proposed method is designed based on LEACH protocol. The area deployed by sensor nodes is divided into two groups based on distance from BS to the nodes. RCH (Relay Cluster Head) relays transmissions from CH to BS if the CH is in the area far away from BS in order to reduce the energy consumption. RCH decides whether to relay the transmissions based on the threshold distance value that is obtained as a output of fuzzy logic system. Our simulation result shows that the application of fuzzy logic Provides the better balancing of energy depletion and Prolonged lifetime of the nodes.