• Title/Summary/Keyword: 무인컨테이너수송차량

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Routing of ALVs under Uncertainty in Automated Container Terminals (컨테이너 터미널의 불확실한 환경 하에서의 ALV 주행 계획 수립방안)

  • Kim, Jeongmin;Lee, Donggyun;Ryu, Kwang Ryel
    • Journal of Navigation and Port Research
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    • v.38 no.5
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    • pp.493-501
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    • 2014
  • An automated lifting vehicle(ALV) used in an automated container terminal is a type of unmanned vehicle that can self-lift a container as well as self-transport it to a destination. To operate a fleet of ALVs efficiently, one needs to be able to determine a minimum-time route to a given destination whenever an ALV is to start its transport job. To find a route free from any collision or deadlock, the occupation time of the ALV on each segment of the route should be carefully scheduled to avoid any such hazard. However, it is not easy because not only the travel times of ALVs are uncertain due to traffic condition but also the operation times of cranes en route are not predicted precisely. In this paper, we propose a routing method based on an ant colony optimization algorithm that takes into account these uncertainties. The result of simulation experiment shows that the proposed method can effectively find good routes under uncertainty.

Design of the Adaptive Fuzzy Control Scheme and its Application on the Steering Control of the UCT (무인 컨테이너 운송 조향 제어의 적응 퍼지 제어와 응용)

  • 이규준;이영진;윤영진;이원구;김종식;이만형
    • Journal of Korean Port Research
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    • v.15 no.1
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    • pp.37-46
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    • 2001
  • Fuzzy logic control(FLC) is composed of three parts : fuzzy rule-bases, membership functions, and scaling factors. Well-defined fuzzy rule-base should contain proper physical intuition on the plant, so are needed lots of experiences of the skillful expert. When membership functions are considered, some parameters on the memberships function such as function shape, support, allocation density should be selected well. The rule of scaling factors is 'scaling'(amplifying or reducing) for both input and output signals of the FLC to fit in the membership function support and to operate the plant intentionally. To get a better performance of the FLC, it is necessary to adjust the parameters of the FLC. In general, the adaptation of the scaling factors is the most effective adjustment scheme, compared with that of the fuzzy rule-base or membership function parameters. This study proposes the adaptation scheme of the scaling factors. When the adaptation is performed on-line, the stability of the adaptive FLC should be guaranteed. The stable FLC system can be designed with stability analysis in the sense of Lyapunov stability. To adapt the scaling factors for the error signals, the concept of the conventional MRAC would be introduced into slightly modified form. A tracking accuracy of the control system would be enhanced by the modified shape and support of the membership function. The simulation is achieved on the pilot plant with the hydraulic steering control of a UCT(Unmanned Container Transporter) of which modeling dynamics have lots of severe uncertainties and modeling errors.

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