• 한국지능시스템학회논문지
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• 제23권5호
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• pp.479-486
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• 2013

항공기의 제어 시스템 설계에 있어 두 가지 어려움이 있다. 즉 항공기의 동적 특성이 비선형 특성을 갖고 있고 그 파라미터 값들이 시간 혹은 비행 조건에 따라 변화하는 시변 특성을 갖고 있다는 점이다. 그럼에도 불구하고 고전적인 제어 이론을 활용한 신뢰성 높고 효율적인 제어 기법들이 계속 개발되어 왔으나 정확한 이론적 분석이 수반되지 않으면 항공기의 성능, 강건성, 그리고 안전성조차도 확보하기 어려운 문제점을 갖는다. 이에 최근에는 퍼지 논리, 신경망, 유전자 알고리즘으로 대표되는 지능 제어 기법을 활용한 항공기 제어 시스템 개발이 시도 되고 있다. 본 논문에서는 기존의 퍼지 논리가 갖고 있는 불확실성에 대한 취약점들을 크게 감소시킬 수 있는 Interval Type-2 퍼지 논리 이론을 기반으로 고속 항공기의 지능형 비행 횡 제어 시스템을 개발하고 컴퓨터 모의실험에 의해 그 효용성을 입증한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.452-455
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• 2004

MSC (Multi-Spectral Camera) system is a remote sensing instrument to obtain high resolution ground image. EOS (Electro-Optic System) for MSC mainly consists of PMA (Primary Mirror Assembly), SMA (Secondary Mirror Assembly), HSTS (High Stability Telescope Structure) and DFPA (Detector Focal Plane Assembly). High performance of EOS makes it possible for MSC system to provide high resolution and high quality ground images. Temperature of the EOS needs to be controlled to be in a specific range in order not to have any thermal distortion which can cause performance degradation. It is controlled by full redundant CPU based electronics. The validity of thermistor readings can be checked because a few thermistors are installed on each control point on EOS. Various kinds of thermal control logics are used to prevent 'Single Point Failure'. Control logic has a few set of database in order not to be corrupted by SEU (Single Event Upset). Even though the thermal control logic is working automatically, it can also be monitored and controlled by ground-station operator. In this paper, various ways of thermal control logic for EOS in MSC will be presented, which include thermal control mode and logic, redundancy design and status monitoring and reporting scheme.

• 대한전기학회논문지:전력기술부문A
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• 제48권2호
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• pp.97-106
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• 1999

This paper proposes the structure and the algorithm of the Fuzzy-Neural Controller(FNNC) which is able to adapt itself to unknown plant and the change of circumstances at the Fuzzy Logic Controller(FLC) with the Neural Network. This Learning Fuzzy Logic Controller is made up of Fuzzy Logic controller in charge of a main role and Neural Network of an adaptation in variable circumstances. This construct optimal fuzzy controller applied to the 2-area load frequency control of power system, and then it would examine fitness about parameter variation of plant or variation of circumstances. And it proposes the optimal Scale factor method wsint three preformance functions( E, , U) of system dynamics of load frequency control with error back-propagation learning algorithm. Applying the controller to the model of load frequency control, it is shown that the FNNC method has better rapidity for load disturbance, reduces load frequency maximum deviation and tie line power flow deviation and minimizes reaching and settling time compared to the Optimal Fuzzy Logic Controller(OFLC) and the Optimal Control for optimzation of performance index in past control techniques.

• 제어로봇시스템학회논문지
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• 제10권2호
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• pp.125-130
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• 2004

This paper describes an approach for synthesizing a Fuzzy Logic Controller(FLC) that combines the benefits of fuzzy logic control and fuzzy logic gain scheduling for the F/A-18 aircraft. Specially, fuzzy rules are utilized on-line to determine the denoralization factor(Κ) of a feedback fuzzy controller based on the dynamic pressure(Q) indicateing the region of the flight envelop the aircraft is operating in. Simulation results demonstrate that the proposed FLC provides excellent compensation for time-varying and/or nonlinear characteristics of the aircraft, and that it also exhibits satisfactory robustness with noisy air data sensors.

• 한국정밀공학회지
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• 제6권2호
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• pp.30-39
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• 1989

Variable structure control (VSC) systems control the state vectors using sliding regime (SR) constructed switching logic, switching plane and control law. Saturation function switching logic is used to improve the drawback which occurs in traditional sign function switching logic. Switching plane with time-varying parameter is proposed to improve the drawback which occurs in switching plane with constant parameter and it is suggested the control law which has time-varying parameter. The stability of VSC system controlled by proposed time-varying SR is discussed, and the good control behavior was shown through computer simulation using proposed SR.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.857-862
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• 1992

An elevator group supervisory control logic is investigated to supervise multiple elevators, ensuring their efficient operations. In this paper, a predictive fuzzy control logic of group elevator system is developed for coping with multiple control objects and uncertainty of system state. Simulation of this control logic shows considerable improvements of system performance by the reduction of average waiting time and long wait rate.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.845-847
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• 2015

A suspending force control based on fuzzy logic control is proposed to apply on a novel hybrid bearingless switched reluctance motor(BLSRM) which has separated torque and suspending force pole. Due to the unique structure, the suspending force control system can be easily decoupled from torque control system. In this paper, two fuzzy controller targeted at x-axis direction and y-axis direction are adopted to maintain the shaft at center position, which is very necessary for stable operation of BLSRM. By replacing the traditional PI block with modified fuzzy logic controller, the suspending system can behave a good performance, and the proposed scheme can be verified by simulation results.

• Journal of Advanced Marine Engineering and Technology
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• 제28권5호
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• pp.793-800
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• 2004

The purpose of this study is to develope a servo system with faster and more accurate response. This paper describes a method of approximate reasoning for fuzzy control of servo system based on the decomposition of $\alpha$-level fuzzy sets. We propose that fuzzy logic algorithm is a body from fuzzy inference to defuzzificaion cases where the output variable u directly is generated PWM The effectiveness for robust and faster response of the fuzzy control scheme are 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 is demonstrated successfully.

• Journal of Power Electronics
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• 제12권2호
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• pp.305-316
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• 2012

The paper presents an accurate loss model based controller of an induction motor to calculate the optimal air gap flux. The model includes copper losses, iron losses, harmonic losses, friction and windage losses, and stray losses. These losses are represented as a function of the air gap flux. By using the calculated optimal air gap flux compared with rated flux for speed sensorless indirect vector controlled induction motor, an improvement in motor efficiency is achieved. The motor speed performance is improved using a fuzzy logic speed controller instead of a PI controller. The fuzzy logic speed controller was simulated using the fuzzy control interface block of MATLAB/SIMULINK program. The control algorithm is experimentally tested within a PC under RTAI-Linux. The simulation and experimental results show the improvement in motor efficiency and speed performance.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.1264-1272
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• 1993

The software for unmanned control of three row typed rice combine has been developed using fuzzy logic. Three fuzzy variables were used : operating status of combine, steering, and speed. Eleven fuzzy rules were constructed and the eleven linguistic variables were used for the fuzzy rules. Six sensors were use of to get input values and sensor input values were quantified into 11 levels. The fuzzy output was infered with fuzzy inferrence which uses the correlation product encoding , and it must have been defuzzified by the method of center of gravity to use it for the control. The result of performance test using graphic simulation showed that the intelligently unmanned control of a rice combine was possible using fuzzy logic control.