• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2004.11a
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• pp.223-229
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• 2004

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1699-1704
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• 2018

In this paper, proposed a method to improve of control characteristics for power facility using the adaptive sizing of fuzzy inference method. In the use of the controller based the fuzzy logic, a basic mamdani fuzzy controller is applied. However, when the maximum value and the minimum value have to taken, the fuzzy controller can not take a normal value because of formalized grouping form. In this paper, we combine the conventional methods with single valued sets to compensate for the disadvantage caused by the mamdani method control. Simulation results show that the proposed method has better overshoot and steady state arrival time than the conventional control method.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.521-526
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• 2012

The performance of arrow from a manufacturing process depends on arrow's trajectory(archer's paradox) and intensity of an impact points. Especially, when conducting a shooting experiment over and over in the same experiment condition, the intensity of impact point is an objective standard to judge the performance of the arrow. However, the analysis method for the impact point is not enough, a previous research of the arrow's performance has been focused on a skill to optimize a manufacturing variables(feathers of an arrow, barb of an arrow, arrow's shaft, weight, external diameter, spine). In this paper, We propose measurement system of arrow's impact point with Mamdani fuzzy inference system and similarity of polygon for automation of impact point's measurement. Measuring the impact point data of the arrow moving with a high speed(approximately 275km/h) by using line laser and photo diode array, then the measured data are mapped to arrow's impact point with fuzzy inference and similarity of polygon.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1591-1598
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• 2008

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. In this paper, we propose Z. Cao's fuzzy inference method with learning ability which is used a gradient descent method in order to improve the performances. It is hard to determine the relation matrix elements by trial and error method. Because this method is needed many hours and effort. Simulation results are applied nonlinear systems show that the proposed inference method using a gradient descent method has good performances.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.193-196
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• 2008

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. In this paper, we propose 2. Cao's fuzzy inference method using learning ability witch is used a gradient descent method in order to improve the performances. Because it is difficult to determine the relation matrix elements by trial and error method which is needed many hours and effort. Simulation results are applied linear and nonlinear system show that the proposed inference method has good performances.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.91-95
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• 2004

In this paper, we propose a fuzzy controller for the evaluation of the quantization parameters in the H.263 coder. Our method adopts the Mamdani method for fuzzification and adopts the centroid method for defuzzification respectively. The inputs are variance, entropy in the spatial domain, current motion vector and previous motion vector in the temporal. Fuzzy variables are determined to be compatible in visual characteristics and fuzzy membership function is induced and then, FAM banks are designed to reduce the number of rules. In this paper, fuzzy quantization has been applied to a practical video compression. This results show that the quality of decode image enhances and the rate control method using fuzzy quantization is effective.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1684-1690
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• 2003

In this paper, we proposed a fuzzy controller for the evaluation of the quantization Parameters in the H.263 coder to optimize the subjective quality of each coded frame, keeping the transmission rate constant. We adopted the Mamdani method for fuzzification and the centroid method for defuzzification. The energy and entropy are correlated to features of the HVS in spatial domain, while motion vectors are used to estimate the temporal characteristics of the signal. And then, the fuzzy inputs adapted the variance and the entropy in spatial domain, and the motion vector in temporal domain. We induced the fuzzy membership function and decided the fuzzy relevance to be compatible in visual characteristics. And then, we designed FAM banks. The fuzzy technology has been applied to a practical video compression. This results is obtained an effective rate control technique, an optimum bit allocation and a high subjective quality using fuzzy quantization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.175-178
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• 2008

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.505-513
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• 2009

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.150-159
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• 2010

The approach and landing phase of a re-entry vehicle is composed of Steep Glideslope phase, Circular Flare phase, Flare Maneuver phase. The trajectory planning algorithm with geometric parameters is studied in this paper for on-board trajectory planning. This algorithm generate reference trajectory rapidly considering safe landing of re-entry vehicle. In this paper, the Mamdani Fuzzy PD type controller for longitudinal and lateral control is designed which has robustness of nonlinear system. In addition, the simulation is performed including initial downrange and crossrange errors, and the results shows that the proposed fuzzy logic controller has good performance.