• 제목/요약/키워드: Control Track

검색결과 1,290건 처리시간 0.026초

콘크리트궤도 유지보수기준 정립을 위한 연구방향 (Research directions for maintenance criteria in Slab Track)

  • 엄종우;이명석;권진수;김수정
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2011년도 춘계학술대회 논문집
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    • pp.979-987
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    • 2011
  • The Ballast Track has been widely applied in traditionally due to low initial cost and abundant elastic property. But the disadvantages of Ballast track are; labor-intensive and costly maintenance, weak in high-speed and heavy axial load, in additionally need wide cross section of tunnel and massive substructure in viaduct. Therefore, recent applications tend to more and more towards slab track such as Gyeungbu high speed rail and existing line. The slab track increased the stability, resistance and durability of track, and save maintenance cost compare to the Ballast Track. But the slab track have weakness of track elongation by sub-ballast differential settlement and that threat safety of train operation. Therefor the slab track need to prevent cracks in concrete ballast for insure the durability of slab track. In this paper, review main items and its expected effects of the slab track maintenance standards that control sub-ballast settlement and concrete ballast cracks.

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퍼지 로직에 의한 궤도차량의 지능제어시스템 설계 (Intelligent control system design of track vehicle based-on fuzzy logic)

  • 김종수;한성현;조길수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.131-134
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    • 1997
  • This paper presents a new approach to the design of intelligent control system 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 on 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.

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K1-궤도차량의 운동제어를 위한 퍼지-뉴럴제어 알고리즘 개발 (Development of Fuzzy-Neural Control Algorithm for the Motion Control of K1-Track Vehicle)

  • 한성현
    • 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.

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An Adaptive Autopilot for Course-keeping and Track-keeping Control of Ships using Adaptive Neural Network (Part II: Simulation Study)

  • Nguyen Phung-Hung;Jung Yun-Chul
    • 한국항해항만학회지
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    • 제30권2호
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    • pp.119-124
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    • 2006
  • In Part I(theoretical study) of the paper, a new adaptive autopilot for ships based on Adaptive Neural Networks was proposed. The ANNAI autopilot was designed for course-keeping, turning and track-keeping control for ships. In this part of the paper, to show the effectiveness and feasibility of the ANNAI autopilot and automatic selection algorithm for learning rate and number of iterations, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented. Additionally, the results of the previous studies using Adaptive Neural Network by backpropagation algorithm are also showed for comparison.

An Adaptive Autopilot for Course-keeping and Track-keeping Control of Ships using Adaptive Neural Network (Part I: Theoretical study)

  • NGUYEN Phung-Hung;JUNG Yun-Chul
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2005년도 추계학술대회 논문집
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    • pp.17-22
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    • 2005
  • This paper presents a new adaptive autopilot for ships based on the Adaptive Neural Networks. The proposed adaptive autopilot is designed with some modifications and improvements from the previous studies on Adaptive Neural Networks by Adaptive Interaction (ANNAI) theory to perform course-keeping, turning and track-keeping control. A strategy for automatic selection c! the neural network controller parameters is introduced to improve the adaptation ability and the robustness of new ANNAI autopilot. In Part II of the paper, to show the effectiveness and feasibility of the proposed ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented.

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An Adaptive Autopilot for Course-keeping and Track-keeping Control of Ships using Adaptive Neural Network (Part II: Simulation study)

  • NGUYEN Phung-Hung;JUNG Yun-Chul
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2005년도 추계학술대회 논문집
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    • pp.23-28
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    • 2005
  • In Part I (theoretical study) of the paper, a new adaptive autopilot for ships based on Adaptive Neural Networks was proposed. The ANNAI autopilot was designed for course-keeping, turning and track-keeping control for ships. In this part of the paper, to show the effectiveness and feasibility of the ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented. Additionally, the results of the previous studies using Adaptive Neural Network by backpropagation algorithm are also showed for comparison.

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An Adaptive Autopilot for Course-keeping and Track-keeping Control of Ships using Adaptive Neural Network (Part I: Theoretical Study)

  • Nguyen Phung-Hung;Jung Yun-Chul
    • 한국항해항만학회지
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    • 제29권9호
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    • pp.771-776
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    • 2005
  • This paper presents a new adaptive autopilot for ships based on the Adaptive Neural Networks. The proposed adaptive autopilot is designed with some modifications and improvements from the previous studies on Adaptive Neural Networks by Adaptive Interaction (ANNAI) theory to perform course-keeping, turning and track-keeping control. A strategy for automatic selection of the neural network controller parameters is introduced to improve the adaptation ability and the robustness of new ANNAI autopilot. In Part II of the paper, to show the effectiveness and feasibility of the proposed ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances will be presented.

Seismic Performance and Vibration Control of Urban Over-track High-rise Buildings

  • Ying, Zhou;Rui, Wang;Zengde, Zhang
    • 국제초고층학회논문집
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    • 제11권3호
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    • pp.207-219
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    • 2022
  • During the structural design of urban over-track high-rise buildings, two problems are most likely encountered: the abrupt change of story stiffness between the podium and the upper towers, as well as the demand for train-induced vibration control. Traditional earthquake-resistant structures have to be particularly designed with transfer stories to meet the requirement of seismic control under earthquakes, and thus horizontal seismic isolation techniques are recommended to solve the transfer problem. The function of mitigating the vertical subway-induced vibration can be integrated into the isolation system including thick rubber bearings and 3D composite vibration control devices. Engineering project cases are presented in this paper for a more comprehensive understanding of the engineering practice and research frontiers of urban over-track high-rise buildings in China.

궤도차량의 동적 궤도장력 조절시스템을 위한 시뮬레이션 툴 구축 (Simulation Tool Development for Dynamic Tracked Tensioning System in Tracked Vehicles)

  • 김일민;김민철;임훈기;허건수
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2002년도 춘계학술대회 논문집
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    • pp.76-81
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    • 2002
  • The characteristics of the track are important concerning the mobility of tracked vehicles. It can be represented in terms of the track tension and maintaining the track tension adequately guarantees the stable and improved driving of the tracked vehicles. The track tension must be known in order to be controlled and it needs to be estimated in real-time because it is difficult to be measured. The tension around idler and sprocket can be controlled by the frizzy logic control system base on the estimated values. Dynamic Track Tensioning System(DTTS) which is estimating and controlling the track tension. In this paper, simulation tool is developed in order to apply the DTTS to real battle tanks. To construct the simulation tool, the Modeling the tracked vehicle, constructing estimation system, and designing controller should be achieved first and then all subsystem should be organized in one. The simulation tool make the RecurDyn model of tracked vehicle, which is plant model, and the control system exchange their data simultaneously. Simulation with many kinds of driving conditions and road conditions is carried out and the results are interpreted. The interpretation provides necessary information to apply the DTTS to real battle tanks.

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해양환경에서 선박 추적을 위한 라이다를 이용한 궤적 초기화 및 표적 추적 필터 (Track Initiation and Target Tracking Filter Using LiDAR for Ship Tracking in Marine Environment)

  • 황태현;한정욱;손남선;김선영
    • 제어로봇시스템학회논문지
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    • 제22권2호
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    • pp.133-138
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    • 2016
  • This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.