• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 추계학술대회 논문집
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• pp.82-87
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• 1997

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, 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 performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 제어로봇시스템학회논문지
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• 제16권9호
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• pp.905-912
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• 2010

Modern version of advanced supersonic fighter have ATCS (Automatic Thrust Control System) to maximum flight safety, fuel efficiency and mission capability the integrated advanced autopilot system such as TFS (Terrain Following System), GCAS (Ground Collision Avoidance System) and AARS (Automatic Attitude Recovery System) and etc. This paper addresses the design and verification of ATCS based on advanced supersonic trainer in HILS (Hardware In the Loop Simulator) with minimum hardware modification to reduce of development cost and maintain of system reliability. The function of ATCS is consisted of target speed hold mode in UA (Up and Away) and angle of attack hold mode in PA (Power Approach). The real-time pilot evaluation reveals that pilot workload is minimized in cruise and approach flight stage by ATCS.

• 한국공작기계학회논문집
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• 제11권4호
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• pp.62-67
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized loaming 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 performing the computer simulation for trajectory tucking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 한국산업융합학회 논문집
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• 제17권2호
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• pp.69-76
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• 2014

This paper proposes a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, 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 performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.235-240
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, 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 performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.207-212
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• 2004

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, 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 performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 한국자동차공학회논문집
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• 제14권2호
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• pp.9-15
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• 2006

Experiments are conducted to compare fuel economy of FTP-75 mode on two different lock-up conditions; (A) Lock-up on at engine speed of 1,200(rpm) and above for 3rd & 4th gear, (B) Lock-up on at engine speed of 1400rpm and above for 4th gear only. As a result, case A had better fuel economy about 2.75(%) than case B for FTP-75 mode. Simulation(CRUISE, AVL) study is also carried out in order to estimate the effect of Lock-up control strategy for vehicle fuel economy. The fuel economy simulation result agrees with the measured fuel economy within error of 2(%). The improved Lock-up control strategy is proposed by simulation.

• 한국산학기술학회논문지
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• 제21권1호
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• pp.457-467
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• 2020

세계적으로 환경문제에 관한 우려가 급증하여, 세계 각국이 온실가스 연비 규제를 강화하고 있다. 연비향상을 위해 첨단 운전자 지원 시스템을 이용한 연구를 통하여, 운전자의 편의를 위해 다양한 첨단 운전자 지원 시스템을 개발하고 있다. 그중 ACC, LKAS, AEB 등의 시스템에 대한 연구가 활발하다. ACC의 목적은 차량의 종 방향 속도와 거리를 제어하고 운전자의 부하를 최소화하여 사고 예방과 방지에 유용한 시스템으로 평가되고 있다. 이러한 관점에서 본 논문은 선행연구에서 제안한 국내도로 환경을 고려한 시나리오와 거리에 대한 함수로 안전성을 평가할 수 있는 수학적 방법을 활용한다. 또한, 제안한 시나리오를 기반으로 시뮬레이션과 실도로 실차시험을 진행한 뒤, 이론수식을 활용한 이론 계산값, 시뮬레이션과 실도로 실차시험의 상대거리의 비교분석을 통하여 ACC의 기능적인 안전성을 검증하고자 한다. 이러한 방법을 통하여 많은 회사들이 ACC의 개발 단계에서 시나리오, 수식, 시뮬레이션을 활용하여 안전성 평가방법으로 활용할 수 있을 것으로 예상된다.

• 자동차안전학회지
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• 제14권2호
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• pp.57-69
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• 2022

Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver's driving fatigue through the control of the vehicle's longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results.

• 한국항공운항학회지
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• 제22권3호
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• pp.8-14
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• 2014

Arrival management is a tool which provides efficient flow of traffic and reduces ATC workload by determining aircraft's sequence and schedules while they are in cruise phase. As a decision support tool, arrival management should advise on air traffic control service based on the understanding of human factor of its user, air traffic controller. This paper proposed a prediction model for air traffic controller sequencing strategy by analyzing the historical trajectory data. Statistical analysis is used to find how air traffic controller decides the sequence of aircraft based on the speed difference and the airspace entering time difference of aircraft. Logistic regression was applied for the proposed model and its performance was demonstrated through the comparison of the real operational data.