• 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.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.707-714
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• 2000

For self-guiding track-type orchard sprayer, a low-cost steering controller was developed using two ultrasonic sensors, two DC motors and 80196kc microprocessor. The operating principle of controller was to travel the sprayer between artificial targets such as wood stick placed every 1 m along both sides of the demanded path of speed sprayer. Measuring distances to both targets ahead with the ultrasonic sensors mounted on the front end of sprayer, the controller could determine how much offset the position of sprayer was laterally. Then the steering angle was calculated to actuate DC motors connected to the steering clutches, where the fuzzy control algorithm was used. Equipped with the controller developed in this research, the sprayer could be traveled along demanded path, the centerline between targets, at speeds of up to 0.4m/sec with an accuracy of ${\pm}$20cm.

• 한국지능시스템학회논문지
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• 제12권6호
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• pp.517-523
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• 2002

본 논문에서는 자연언어를 이용하는 인간의 학습방법에 기초한 LIBL방법의 실용화를 위하여 음성지시기반학습(VIBL : Voice Instruction Based Learing)을 선박의 조타 시스템, 주기원격제어시스템(MERCS), 윈치기기에 적용하여 항해사의 조타명령과 같은 언어적 지시가 조타수를 경유하여 수행되는 과정을 대체하는 VIBL법을 이용한 조타기, 주기 원격 조종장치, 윈치 기기를 제어하는 시스템을 제안하고자 한다. 구체적인 연구방법으로는 조타수의 적절한 조타조작모델을 퍼지추론 규칙을 이용하여 구현하고, 적절한 의미소 및 평가규칙을 제시한 언어지시 기반 학습방법을 선박의 조타시스템에 적용하여 지시자의 음성언어지시에 보다 효율적으로 응답하는 지능형 조타기 제어 시스템을 구현하고, 지시자의 음성지시를 인식하여 주기 원격 조종 장치와 윈치 기기를 제어하는 시스템을 구현한다. 음성언어지시를 인식하여 텍스트로 변환하기 위한 기법과 퍼지추론을 이용하여 조타수의 경험을 바탕으로 한 조타 조작 모델을 구축하였고, 지능형 조타 시스템을 위한 타각, 방위도달시간, 정상상태의 의미소를 제안하여, 조타수 조작 모델 규칙을 수정하기 위한 평가규칙을 제시하였다. 또한, 구현된 음성인식 선박조종 시뮬레이터에 적용하여 그 유효성을 확인하였다.

• 한국정밀공학회지
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• 제20권5호
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• pp.82-91
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• 2003

Vehicle dynamics control (VDC) has been a breakthrough and become a new terminology for the safety of a driver and improvement of vehicle handling. This paper examines the usefulness of a brake steer system (BSS), which uses differential brake forces for steering intervention in the context of VDC, In order to help the car to turn, a yaw moment can be achieved by altering the left/right and front/rear brake distribution. The steering function achieved through BSS can then be used to control lateral position in an unintended road departure system. An 8-DOF non-linear vehicle model including STI tire model will be validated using the equations of motion of the vehicle, and the non-linear vehicle dynamics. Since fuzzy logic can consider the nonlinear effect of vehicle modeling, fuzzy controller is designed to explore BSS feasibility, by modifying the brake distribution through the control of the yaw rate of the vehicle. The control strategies developed will be tested by simulation of a variety of situation; the possibility of VDC using BSS is verified in this paper.

• Journal of Advanced Marine Engineering and Technology
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• 제34권1호
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• pp.109-115
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• 2010

본 논문은 퍼지 제어를 통한 이동용 로봇에 대한 추적 제어에 대해서 다루고 있다. 이동용 로봇은 Mamdani 형식의 퍼지 제어기로 제어 된다. 퍼지 제어기에 있어서 이동용 로봇과 목표 사이의 각도와 각도의 변화율이 입력으로 사용되고, 출력으로 조향각이 추론되어 제어입력이 된다. 퍼지 규칙은 전문가의 경험적 지식을 참조하여 7개를 사용하였다. 또한 퍼지 제어기 설계에 있어서 하나의 관심 분야인 환산계수(scaling factor) 조정 방법에 대해 제안한다. 본 논문에서는 이를 위해 파라미터 최적화 분야에서 잘 알려진 실수코딩 유전알고리즘을 적용하였다. 시뮬레이션을 통해 다양한 초기 조향각이 주어진 경우, 목표치에 대한 추적 안정성을 보여 퍼지 제어기의 유효성이 확인된다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.142-147
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• 1999

This paper presents a new approach to the dynamic control technique for track vehicle system using neural network-fuzzy control method. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.

• 전자공학회논문지B
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• 제33B권7호
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• pp.21-31
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• 1996

An intelligent integrated control system is designed for the active steering and the left/right traction force distribution control of electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additively utilized for the estimator to correctly find cornering forece. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.133-139
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• 1997

This paper presents a new approach to the dynamic control technique for track vehicle system using neural network-fuzzy control method. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is propored a learning controller consisting of two neural network-fuzzy based on independent resoning and a connection net with fixed weights to simply the neural network-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 추계학술대회 논문집
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• pp.70-75
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• 1997

This paper proposes a new approach to the design of fuzzy-neuro control for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• Journal of Biosystems Engineering
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• 제25권1호
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• pp.55-62
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• 2000

Autonomous farm operation needs to be developed for safety, labor shortage problem, health etc. In this research, an autonomous tractor for tillage was investigated using machine vision and a fuzzy logic controller(FLC). Tractor heading and offset were determined by image processing and a geomagnetic sensor. The FLC took the tractor heading and offset as inputs and generated the steering angle for tractor guidance as output. A color CCD camera was used fro the image processing . The heading and offset were obtained using Hough transform of the G-value color images. 15 fuzzy rules were used for inferencing the tractor steering angle. The tractor was tested in the file and it was proved that the tillage operation could be done autonomously within 20 cm deviation with the machine vision and the FLC.