본 논문에서는 항만 자동화를 위해 새로이 제안된 리니어 모터 기반 컨테이너 이송시스템에 지능제어기법을 이용하여 그 정밀도를 향상시키고자 한다. LMCTS(Linear Motor-based Container Transfer System)는 스케일의 거대함 때문에 일반 리니어 모터에서 중요시 되지 않는 정지마찰력과 디텐트럭(detent force)이 정밀제어에 큰 문제가 된다. 특히, 컨테이너 적제유무에 따라 시스템 자체가 급격히 변하므로 기존의 PID형 제어기로는 좋은 성능을 얻기 어렵다. 따라서 본 논문에서는 같은 구조를 갖는 두 개의 DR-FNN(Dynamically- constructed Recurrent Fuzzy Neural Network)를 제어기와 에뮬레이터로 구성하여 이러한 문제를 해결하고자 하였다.

LMTT(Linear Motor-based Transfer Technology)는 항만 자동화를 위한 컨테이너 터미널용 수평 이송 장치이며, rail과 shuttle car(mover)에 부착된 stator module로 구성된 PMLSM(Permanent Magnetic Linear Synchronous Motor)에 의해 구동된다. 본 논문은 inner beam과 outer beam의 높이비가 LMTT용 shuttle car의 frame 강도 및 강성에 미치는 영향을 살펴보았다. 설계변수는 inner beam의 단면형상 및 높이비로 설정하였으며, 유한요소해석을 통하여 설계변수가 frame의 강도 및 강성에 미치는 영향을 살펴보았다.

와이어 로프는 엘리베이트, 건설현장의 리프트, 현수교 등 다양한 산업 현장에 응용되어 지고 있다. 특히, 크레인의 와이어 로프는 컨테이너 이송에 중용한 요소로서 컨테이너 이송 시 로프에 결함이 발생한다면 안전사고, 생산성 저하에 따른 경제력 손실 그리고 컨테이너 터미널의 경쟁력 손실 등 여러 가지 문제점이 초래된다. 이러한 문제점을 해결하기위해 원격 크레인 와이어 로프 결함 탐지 시스템을 개발하였으며, 본 시스템은 크게 결함 탐지부, 신호 처리부, 원격 모니터링부로 구성되어져 있다. 측정된 신호는 외부적 환경으로부터 노이즈를 가지게 되는데 원신호로부터 이러한 노이즈를 제거하기 위하여 이산 웨이브렛 변환을 적용하였다. 그 결과 와이어 로프 결함을 탐지하는데 있어서 좀더 쉽게 결함을 판별할 수 있었다. 결론적으로 이러한 시스템의 개발은 와이어로프의 교체 시기 연장으로 항만의 비용을 절감할 수 있으며, 경쟁력 향상 그리고 엘리베이터, 리프트 등 다양한 산업현장에 이러한 시스템을 적용할 수 있다.

최근에, 자동화 크레인 제어 시스템은 빠른 속도와 신속한 수송이 요구되어 지고 있다. 따라서, 컨테이너가 초기좌표에서 최종좌표로 이동될 때 컨테이너 경로는 최소시간에 흔들림 없이 설계되어야 한다. 이를 위해 본 연구에서는 최종 좌표까지 이동에서 충돌을 피하기 위하여 충돌방지 경로를 계산하였다. 그리고, 정확한 주행 제어를 위해서 신경회로망 예측 PID제어기를 구성하였다. 제안된 예측제어 시스템은 PID 파라미터를 생산하기 위하여 신경회로망 예측기, PID 제어기 그리고 신경회로망 자기 동조기로 구성하였다 크레인 시스템을 통한 시뮬레이션 분석에서 다른 기존의 제어기들 보다 우수한 제어 수행을 증명하였다.

In this paper, an improved high efficiency gantry crane for container transportation is designed. The basic concept of the designed crane can be used with modification of the classical gantry crane instead of changing lots of them. This crane can reduce the cycle time more than the classical gantry carne. The high efficiency gantry crane can improve the productivity of the container transportation job because of reducing cycle time. The loading and unloading capability are compared with classical crane. The result show that show that the proposed crane has better performances than classical type.

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.

In this study, as the preliminary step for developing an unmanned vehicle to deliver a container-box, we designed and implemented Automatic Guided Vehicle(AGV) Simulator for the purpose of Port Facilities Automation. It is preferable to research the intelligent AGV for delivery all day long. For complementing AGV simulator driving, we used multiple-sensor systems with vision, ultrasonic, IR and adapted the high-speed wireless LAN that satisfies the IEEE 802.11 Standard for bi-directional communication between main processor in AGV and Host computer. Here, we mounted on bottom frame in AGV Pentium-III processor, which combine and compute the information from each sensor system and control the AGV driving, and used the 80C196KC micro-controller to control the actuating and steering motors.

In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied to the driving control of the autonomous guided vehicle(AGV). When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged by the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined through this off-line manner, these parameters are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted more accurately through the on-line fine tuning. The experiment for the control of steering and speed of AGV is performed. The results show that the proposed controller provides better performances than other conventional controllers.

In the biological immunity, the immune system of organisms regulates the antibody and T-cells to protect the attack from the foreign materials which are virus, germ cell, and other antigens, and supports their stable state. It has similar characteristics that has the adaptation and robustness to overcome disturbances and to control the plant of engineering application. In this paper, we build a model of the T-cell regulated immune response mechanism. We have also designed an immune response controller(IRC) focusing on the T-cell regulated immune response of the biological immune system that include both a help part to control the response and a suppress part to adjust system stabilization effect. We show some computer simulation to control the vibration of building structure system with strong wind forces excitation also demonstrate the efficiency of the proposed controller for applying a practical system even with existing nonlinear terms.

During the operation of crane system in container yard, the objective is to transport the load to a goal position as quick as possible without rope oscillation. The container crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. Therefore, we developed an optimal controller which has to control the crane system with disturbances. In this paper, we present a design of optima 2-DOF PID controller for the control of gantry crane which has to control swing motion and trolley position. We used evolution strategy(ES) to tune the parameters of 2-DOF PID controller. It was compared with general PID controller. The computer simulations show that the proposed method has better performances than the other method.