• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.153-159
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• 2009

The steel balls are core elements between inner part and outer part in a bearing system. The degree of goodness of the steel balls has been visually processed by human beings. In this paper we propose a new method that uses image processing algorithm and fuzzy logic theory. We use fuzzy inference engine and fuzzy Choquet integral algorithm in the proposed system. We first distinguish the defects of the steel balls by an image processing algorithm. And then the degree of the defects is classified by a fuzzy logic system. We perform some simulations to show the effectiveness and feasibility of the proposed system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.2
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• pp.99-104
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• 2011

In this paper, the intelligent landscape lighting power control and monitoring system with solar sell generator equipment is proposed. The first, the intelligent landscape lighting power controller is designed using the fuzzy logic control method. And the fuzzy logic controller is used to save power consumption for various reference intensity of the illumination. The second, the GUI monitoring system is presented. It has control and display faculty. And the practical experiment device is used to evaluate the performance criteria of the proposed intelligent landscape lighting power control system with the solar cell power generation equipment. From the experiment results, we present the property of proposed fuzzy controller such as steady state error, the tracking and power consumption characteristic for the reference intensity of illumination. And also we show the superiority of power control as well as the characteristic of GUI monitoring system in the proposed system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.59-70
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• 1995

Output performance improvement using fuzzy logic to the conventional control scheme for a magnetic levitation system is presented in this paper, Adverse characteristics of nonlinearity, unstability, system parameter variation, etc, in the levitation system are partially overcome by the general fuzzy control action. Using a PD type compensator, a coarse framework of output performance is provided to the levitation system. Then a fine regulation to the output performance requirement is obtained by the natural description of the control action in the form of fuzzy logic controller. This control action soothes the adverse characteristics of the levitation system. In this way a better output performance can be obtained in a real time experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2189-2198
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• 1994

In this paper, a self-tuning fuzzy logig controller is implemented to control a DC servo motor by the self-tuning technique based on fuzzy meta-rules with learning in several algorithms to improve the performance of the fuzzy logic controller used in a fuzzy control system. Simulations and experimental results of the self-tuning fuzzy logic controller are compared with those of the fuzzy logic controller to evaluate its performance.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.16-21
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• 2008

In order to protect the environment from the refrigerant pollution, the $CO_2$ may be regarded as one of the most attractive alternative refrigerants for an automotive air-conditioning system. Control methods for a $CO_2$ system should be different because of $CO_2$'s unique properties as a refrigerant. Especially, the high-side pressure of a $CO_2$ system should be controlled for the effective operation of the system. High-side pressure algorithms, which were composed of the pressure setpoint algorithm and the pressure setpoint reset algorithm, were developed. Pressure setpoint algorithms, by using a neural network and by using a least square method, were developed and compared. Pressure setpoint reset algorithms, by using a fuzzy logic and by using a proportional logic, were also developed and compared. Simulation results showed that a least square method was more useful than a neural network for the pressure setpoint algorithm. And a proportional logic was more practical than a fuzzy logic for the pressure setpoint reset algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.268-274
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• 2013

Any new method for controlling a nonlinear system has widely been reported. An inverted pendulum system has typically been used as a target system for demonstrating its usefulness. In this paper, we propose an algorithm to control a flexible joint cart based inverted pendulum system. Two carts are connected with a spring and one is a driving cart and the other is no driving cart with a pole. We here present a system modeling and a good fuzzy logic based control algorithm. We also introduce LQR (Linar Quadratic Regulator) technique for reducing the number of control variables. By using this technique, the number of input variables for a fuzzy logic controller is become only two not six. So the computational complexity is largely reduced. Moreover, a two-input fuzzy logic controller has a control rule table with a skew-symmetric property. And it will lead the design of a single-input fuzzy logic controller. In order to demonstrate the usefulness of the proposed method and prove the superiority of the proposed method, some computer simulations are presented.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.217-218
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• 2006

We propose a method for improving the performance of the Amplitude Shift Keying (ASK) system using a fuzzy logic system for automatically tuning the bandwidth of low pass filter. Instead of a fixed bandwidth of a low pass filter of receiver, the fuzzy logic system is used to automatically adjust the bandwidth. The inputs to the fuzzy logic system are the error and change of error, and output is a bandwidth. Simulation results showed that the proposed system improves considerably on the performance of the fixed bandwidth.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.141.1-141
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• 2001

This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) for a high maneuverable aircraft system, where the gains of FLC are on-line adapted according to the flight condition. Specially, the systematic procedure via root locus technique is carried out for the sellection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields better control performance than the normal (without gain scheduling) fuzzy controller.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.5
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• pp.434-439
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• 2013

It is very difficult to monitor the blind spots that are not recognized by traditional surveillance camera (CCTV) systems, and the surveillance efficiencies are very low though many accidents/events can be solved by the systems. In this paper, the fuzzy logic based sound source localization system using sound strength in the underground parking lot is suggested and the performance of the system is analyzed in order to enhance the stabilization and the accuracy of the localization algorithm in the suggested system. It is confirmed that the localization stabilization of the localization algorithm (SLA_fuzzy) using the fuzzy logic in the suggested system is 4 times higher than that of the conventional localization algorithm (SLA). In addition to this, the localization accuracy of the SLA_fuzzy in the suggested system is 29% higher than that of the SLA.