• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.449-455
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• 2011

In this paper, Proposed controller prevent compressor surge and reduce the acceleration time of the fuel flow control system for turbo-jet engine. Turbo-jet engine controller is designed by applying fuzzy PI+D control algorithm and make an inference by applying Mamdani's inference method and the defuzzification using the center of gravity method. Fuzzy inference results are used as the fuel flow control inputs to prevent compressor surge and flame-out for turbo-jet engine and the controller is designed to converge to the desired speed quickly and safely. Using MATLAB to perform computer simulations verified the performance of the proposed controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.4
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• pp.346-360
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• 1992

This paper proposed a method of identity decision of moving object by the fuzzy inference. Moving object is extracted by the difference picture method and identity decision parameters of moving object are chosen area, perimeter. A/p ratio and vertex. In the brightness variation of 600 Lux-1600Lux, we determined the maximum error often parameters and then generated a fuzzified data. Fuzzified data are generated from the reference image and then decided the identity of extracted parameter by the fuzzy inference using fuzzy production rule. In order to verify validity of proposed method, experiment are performed with a toy car. As a result, it was shown that decision error was less than 4%

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.11-35
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• 1995

In this paper the fuzzy extension for the classical engineering mechanics problems is studied. The governing differential equation is derived for the buckling loads of the columns with uncertain mediums: the their own weight and the flexural rigidity. The columns with one typical end constraint(hinged1 clarnped/free) and the other finite rotational spring with fuzzy constant are considered in numerical examples. The vertex method is used to evaluate the fuzzy functions. The Runge-Kutta method and Determinant Search method are used to solve the differential equation and determine the buckling loads, respectively. The membership functions of the buckling load are calculated. The index of fuzziness to quantitatively describe the propagation of fuzziness is defined. According to the fuzziness of governing factors, the varlation of index of fuzziness for buckling load is investigated, and the sensitivity for the end constraints is analyzed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.181-187
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• 2015

In this study, an LED emotional lighting algorithm optimized to the situation was implemented using fuzzy inference for users in exercise and resting situations in indoor environment. The fuzzy theory was used instead of the conventional simple color temperature control in order to control the colors and color temperatures of LED light sources in line with user environment under complex conditions. An LED emotional lighting system based on fuzzy theory was designed through a combination of colors according to the color and temperature of emotional language based on the user behavior. As a result, the color and color temperature can give a good effect on user's emotions for an emotional lighting that is effective for resting and exercise.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.1-8
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• 2007

In recent, the issues of sensitivity and psychology of human have received much attention from researchers and practitioners. In this paper. we analyze the information of color and location in order to detect the sensitivity and psychology by means of human vision on color space organization in a presented picture. After this process, we propose a method to determine psychology states through the space organization by using a fuzzy membership function which can be used to analyze direction information for the sensitivity. The proposed method is applied to the psychology states based on the space organization of Alschuler and Hattcick's method and to the space organization of Gunnwald's method. As a result, we present that the proposed method is very similar to a pattern classification of Alschuler and Grunwald.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.881-886
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• 2007

Fuzzy inference has the advantage which can process the ambiguous knowledge. However the associated attributes of fuzzy rules are difficult to determine useful and important rules because the redundant attribute of rules is more than enough. In this paper, we propose a method to minimize the number of rules and preserve the accuracy of inference results by using fuzzy relative cardinality after removing unnecessary attributes from rough set. From the experimental results, we can see the fact that the proposed method provides better results (e.g the number of rules) than those of general rough set with the redundant attributes.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.342-347
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• 2003

It is essential to develop an algorithm for the estimate of link travel velocity and for the supply and control of travel information in the context of intelligent transportation information system. The paper proposes the fuzzy logic based prediction of link travel velocity. Three factors such as time, date and velocity are considered as major components to represent the travel situation. In the fuzzy modeling, those factors were expressed by fuzzy membership functions. We acquire position／velocity data through GPS antenna with PDA embedded probe vehicles. The link travel velocity is calculated using refined GPS data and the prediction results are compared with actual data for its accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1149-1158
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• 2004

In this thesis, we created a Fuzzy rule in a Fuzzy logic that are Fuzzy logic which is composed of linguistic rules and Fuzzy inference engine for effective traffic control in ATM networks. The parameters of the Fuzzy rules are adapted to minimize the given performance index in both cases. In other words, the difuzzification value controls the threshold in the buffer to arrival ratio to traffic priority (low or high) using fuzzy set theory for traffic connected after reasoning. Also, show experiment result about rule by MATLAB6.5 and on-line bulid-up to verify validity of created Fuzzy rule. As a result, we can verify that threshold value in buffer is efficiently controlled by the traffic arrival ratio.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.120-125
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• 2005

In this paper, We propose the fuzzy controller for the gain tuning of PID controller The proposed controller doesn't use the crisp output error and rule tables though with a fuzzy inference process in forward fuzzifier, New Fuzzy PID Controller assigns relations and ranges of two variables of PID gain parameters. These new gain parameters are calculated by the fuzzy inference with max-min ranges of Kp and Kd. The Ki parameter is computed automatically between Kp and Kd parameter Is calculated by Ziegler-Nickels tuning rules. Finally we experimented the propose controller by the hydraulic servo motor control system. We can obtained desired results through the good control characteristics.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.2
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• pp.310-316
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• 2003

One of the significant subject in the automatic arc welding is to establish control system of the welding parameters for controlling bead geometry as a criterion to evaluate the quality of arc welding. This paper proposes an inference algorithm for bead geometry in CMA Welding using Neuro-Fuzzy algorithm. The characteristic welding parameters are measured by the circuit composed of hall sensor, voltage divider tachometer, etc. and then the bead geometry of each weld pool is calculated and detected by an image processing with CCD camera and a measuring with microscope. The relationships between the characteristic welding parameters and the bead geometry have been arranged empirically. From the result of experiments, membership functions and fuzzy rules are tuned and determined by the learning of neural network, and then the relationship between actual bead geometry and inferred bead geometry are concluded by fuzzy logic controller. In the applied inference system of bead geometry using Neuro-Fuzzy algorithm, the inference error percent is within -5%∼+4% in case of bead width, -10%∼+10% in bead height, -5%∼+6% in bead area, -10%∼+10% in penetration. Use of the Neuro-Fuzzy algorithm allows the CMA Welding system to evaluate the quality in bead geometry in real time as the welding parameters change.