• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.768-783
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• 2020

Typically, a Dynamic Positioning System (DPS) uses a PID feed-back system, and it often adopts a wind feed-forward system because of its easier implementation than a feed-forward system based on current or wave. But, because a ship's drifting motion is caused by wind, current, and wave drift loads, all three environmental loads should be considered. In this study, a motion predictive control for the PID feedback system of the DPS is proposed, which considers the three environmental loads by utilizing predicted drifted ship positions in the future since it contains information about the three environmental loads from the moment to the future. The prediction accuracy for the future drifted ship position is ensured by adopting deep learning algorithms and a replay buffer. Finally, it is shown that the proposed motion predictive system results in better station-keeping performance than the wind feed-forward system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.480-488
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• 2019

In this paper, we propose an obstacle avoidance system for an unmanned ship to navigate safely in dynamic environments. Also, in this paper, one-dimensional low-cost lidar sensor is used, and a servo motor is used to implement the lidar sensor in a two-dimensional space. The distance and direction of an obstacle are measured through the two-dimensional lidar sensor. The unmanned ship is controlled by the application at a Tablet PC. The user inputs the coordinates of the destination in Google maps. Then the position of the unmanned ship is compared with the position of the destination through GPS and a geomagnetic sensor. If the unmanned ship finds obstacles while moving to its destination, it avoids obstacles through a fuzzy control-based algorithm. The paper shows that the experimental results can effectively construct an obstacle avoidance system for an unmanned ship with a low-cost LiDAR sensor using fuzzy control.

• Journal of Navigation and Port Research
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• v.44 no.2
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• pp.136-143
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• 2020

Maritime autonomous surface ships (MASS) has been developed over the years. But, there are many unresolved problems. To overcome these problems, this study proposes connected ship navigation system. The system comprises a slave ship and a master ship that leads the slave ship. To implement this system, communication network, route planning algorithms, and controllers are designed. The communication network is built using the transmission control protocol/Internet protocol (TCP/IP) socket communication method to exchange data between ships. The route planning algorithms calculate the course and distance of the slave ship using the middle latitude sailing method. Nomoto model is used as the mathematical model of the slave ship maneuvering motion. Then, the autoregressive with exogenous variables (ARX) model is used to estimate the parameters of Nomoto model. Based on the above model, the automatic steering controller is designed using a proportional-derivative (PD) control. Also, the speed controller is designed for the slave ship to maintain constant distance from the master ship. Sea experiments are conducted to verify the proposed system with two remodeled boats.

• Journal of Navigation and Port Research
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• v.31 no.4
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• pp.289-293
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• 2007

In this paper, new application of adaptive neural network to design a ship's Rudder-Roll Damping(RRD) control system is presented Firstly, the ANNAI neural network controller is presented. Secondly, new RRD control system using this neural network approach is developed. It uses two neural network controllers for heading control and roll damping control separately. Finally, Computer simulation of this RRD control system is carried out to compare with a linear quadratic optimal RRD control system; discussions and conclusions are provided. The simulation results show the feasibility of using ANNAI controller for RRD. Also, the necessity of mathematical ship model in designing RRD control system is removed by using NN control technique.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.14-25
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• 2012

Recently, the application and installation of the pod propeller to the cruise ship is dramatically increased. It is because pod propulsion system allows a lot of flexibility in design of the internal arrangement of a ship. To reflect this trend, many researches have conducted to use the pod propeller for the roll stabilization of a ship. In the paper, a roll stabilization controller is designed by using fins and pod propellers as the control actuators for cruise ships. Two kinds of control algorithms are adopted for the roll control system; LQR (Linear Quadratic Regulator) algorithm and frequency-weighted LQR algorithm. Through the numerical simulation, the effect of the turning rate of the pod propeller on the roll control system is analyzed. Analysis of the simulation results indicated that the turning rate of the pod propellers is one of the important parameters which give the significant effects on the roll stabilization.

• Journal of the Society of Naval Architects of Korea
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• v.41 no.4
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• pp.77-84
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• 2004

Active control is regarded as one of the most efficient and economic countermeasures to reduce excessive vibration of ship superstructure. However, it is difficult to find its practical application in real ships in spite that many studies on such systems have been done. In this study, for the practical use of an active control system to reduce ship superstructure vibration, we have developed an active vibration compensator consisting of a mechanical actuator having compact size and expected lifetime over 20 years, its control panel including exclusive signal processing and computing board, sensors to detect phase and vibration, and its operation software providing various user-interface functions. From the performance verification test of the system at a 5,500 TEU container carrier, we have confirmed the system could reduce ship superstructure vibration of a harmonic component of main engine rotating frequency up to 0.1 mm/s.

• Structural Engineering and Mechanics
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• v.30 no.6
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• pp.679-698
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• 2008

On marine vessels, delicate instruments such as navigation radars are normally mounted on ship masts. However the vibrations at the top of mast where the radar is mounted often cause serious deterioration in radar-tracking resolution. The most serious problem is caused by the rotational vibrations at the top of mast that may be due to wind loading, inertial loading from ship rolling and base excitations induced by the running propeller. This paper presents a method of semi-active vibration control using magneto-rheological (MR) dampers to reduce the rotational vibration of the mast. In the study, the classical optimal control algorithm, the independent modal space control algorithm and the double input - single output fuzzy control algorithm are employed for the vibration control. As the phenomenological model of an MR damper is highly nonlinear, which is difficult to analyse, a back- propagation neural network is trained to emulate the inverse dynamic characteristics of the MR damper in the analysis. The trained neural network gives the required voltage for each MR damper based on the displacement, velocity and control force of the MR damper quickly. Numerical simulations show that the proposed control methods can effectively suppress the rotational vibrations at the top of mast.

• Journal of Power System Engineering
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• v.17 no.5
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• pp.94-99
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• 2013

This paper presents some experimental results about Position Mooring (PM) system applied to the barge ship. In PM operation, the station keeping in surge, sway of vessel is provided by the mooring system. In this paper, a system, consisting of a barge vessel and mooring lines, is mathematically modeled. The position and orientation of vessel is controlled by changing the tensions in the mooring lines. The PID control strategy is applied to evaluate the efficiency of proposed system. Experimental result which corresponds to the applied control strategy is presented and discussed.

• Journal of the Korean Institute of Navigation
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• v.20 no.3
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• pp.65-71
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• 1996

Recently, the Track Control System which was separated from the Course Control System so-called Auto-Pilot has been developed for track-keeping in coastal area. From this year, the NAV Sub-committee in IMO commenced to consider the Performance Standard for the Track Control System vigorously. This system will be integrated with ECDIS and IBS so that captain/officers should analysis ship's motion characteristics accurately in the route planning using the electronic nautical charts. In this paper, a new Route Analysis Algorithm using fuzzy reasoning in route planning was proposed for 2, 700 TEU container ship. In order to verify the track-keeping, the author established a ship mathematical model and executed the simulation of the Route Analysis Algorithm at on-line condition with Pentium PC. The results of ship trajectories of the Route Analysis Algorithm were found to be effective to get track control automatically.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.67-74
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• 2006

In this paper, an adaptive neural network controller and its application to automatic berthing control of ship is presented. The neural network controller is trained online using adaptive interaction technique without any teaching data and off-line training phase. Firstly, the neural networks used to control rudder and propeller during automatic berthing process are presented. Finally, computer simulations of automatic ship berthing are carried out to verify the proposed controller with and without the influence of wind disturbance and measurement noise.