• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1907-1908
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• 2006

Recently, an automatic crane control system is required with high speed and rapid transportation. Therefore, when container is transferred from the initial coordinate to the finial coordinate, the container paths should be built in terms of the least time and without sway. Therefore, we calculated the anti-collision path for avoiding collision in its movement to the finial coordinate in this paper. And we constructed the neural network predictive two degree of freedom PID controller to control the precise navigation. The proposed predictive control system is composed of the neural network predictor, two degree of freedom PID controller, neural network self-tuner which yields parameters of two degree of freedom PID. We analyzed crane system through simulation, and proved excellency of control performance over the conventional controllers.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2456-2458
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• 2003

Recently, an automatic crane control system is required with high speed and rapid transportation. Therefore, when container is transferred from the initial coordinate to the finial coordinate, the container paths should be built in terms of the least time and without sway. Therefore, we calculated the anti-collision path for avoiding collision in its movement to the finial coordinate in this paper. And we constructed the neural network predictive two degree of freedom PID (NNPPID) controller to control the precise navigation. The proposed Predictive control system is composed of the neural network predictor, two degree of freedom PID(TDOFPID) controller, neural network self-tuner which yields parameters of TDOFPID. We analyzed crane system through simulation, and proved excellency of control performance over the conventional controllers.

• Journal of Navigation and Port Research
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• v.26 no.5
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• pp.537-542
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• 2002

Recently, an automatic crane control system is required with high speed and rapid transportation. Therefore, when container is transferred from th intial coordinate to the finial coordinate, the container paths should be built in terms of the least time and no swing. So in this paper, we calculated the anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the neural network predictive PID (NNPPID) controller to control the precise navigation. The proposed predictive control system is composed of the neural network predictor, PID controller, neural network self-tuner which yields parameters of PID. Analyzed crane system through simulation, and proved excellency of control performance than other conventional controllers.

• Journal of Ocean Engineering and Technology
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• v.20 no.6 s.73
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• pp.114-122
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• 2006

The most important thing in the container terminal is to handle the cargo effectively in a limited time. To achieve this objective, many strategies have been introduced and applied. If we consider the automated container terminal, it is necessary that the cargo handling equipment is equipped with more intelligent control systems. From the middle of the 1990s, an automated rail-mounted gantry crane (RMGC) and rubber-tired gantry crane (RTG) have been developed and widely used to handle containers in the yards. Recently, in these cranes, equipment like CCD cameras and sensors have been mounted to cope with the automated terminal environment. In this paper, we try to support the development of more intelligent automated cranes that make the cargo handling be performed effectively in the yards. For this plant, we ought to consider modeling, tracking control, anti-sway system design, skew motion suppressionand complicated motion control and suppressing problems. In this paper, the system modeling and a tracking control approach are discussed, based on a two-degree-of-freedom (2DOF) servo-system design. From the simulation results, the good control performance of the designed control system is evaluated.

• Journal of Power System Engineering
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• v.11 no.4
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• pp.103-108
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• 2007

In general, the swing motion of the crane is controlled and suppressed by activating the trolley motion. In many papers reported by us, we suggested a new type of anti-sway control system of the crane. In the proposed control system, a small auxiliary mass(moving-mass) is installed on the spreader and the swing motion is controlled by moving the auxiliary mass. The actuator reaction against the auxiliary mass applies inertial control forces to the container in order to reduce the swing motion in the desired manner. The measuring system is based on laser sensor or others. However it is not so useful in real world. Especially, in this paper, the image sensor is used to measures the motions of the spreader and the measured data are fed back to the controller in real time. The applied image processing technique is a kind of robust template matching method which is named Vector Code Correlation (VCC) and devised to consider the real environmental conditions. And the $H_{\infty}$ based control technique is applied to suppress swing motion of the crane. And the experimental result shows that the proposed measurement system based on image sensor and control system is useful and robust to disturbances.

• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.747-753
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• 2005

In this paper, as an anti-sway control strategy of container cranes, we investigate a variable structure control in which the moving load follows a given trajectory, whereas both the trolley and hoist controllers achieve their positioning problems. It is crucial, in an automated container terminal, that collisions should be avoided during the transference of containers from one place to another. It is also necessary, in the case of a quay crane, to select suitable loading and unloading trajectories of containers, so that possible collisions with surrounding obstacles are avoided. After a brief introduction of the mathematical model, a robust control scheme (i.e., a second-order sliding mode control that guarantees a fast and precise transference and a suppression of the resulted swing) is presented. Despite model uncertainties and unmodeled actuators dynamics, the swing suppression from the given trajectory is obtained by constraining the system motion on suitable sliding surfaces, which include both the desired path and the swing angle. The proposed controller has been tested with a laboratory-size pilot crane. Experimental results are provided.