• Journal of Advanced Research in Ocean Engineering
• /
• 제2권4호
• /
• pp.192-201
• /
• 2016

This study examined a PD controller and its application to automatic berthing control of an unmanned surface vehicle (USV). First, a nonlinear mathematical model was established for the maneuvering of the USV in the presence of environmental forces. A PD control algorithm was then applied to control the rudder and propeller during an automatic berthing process. The algorithm consisted of two parts, namely the forward velocity control and heading angle control. The control algorithm was designed based on longitudinal and yaw dynamic models of the USV. The desired heading angle was obtained using the "line of sight" method. Finally, computer simulations of automatic USV berthing were performed to verify the proposed controller subjected to the influence of disturbance forces. The results of the simulation revealed a good performance of the developed berthing control system.

• 한국해양공학회지
• /
• 제37권3호
• /
• pp.122-128
• /
• 2023

Autonomous berthing is a crucial technology for autonomous ships, requiring optimal trajectory planning to prevent collisions and minimize time and control efforts. This paper presents a two-phase, two-point boundary value problem (TPBVP) strategy for creating an optimal berthing trajectory for a twin-propeller, twin-rudder ship with autonomous berthing capabilities. The process is divided into two phases: the approach and the terminal. Tunnel thruster use is limited during the approach but fully employed during the terminal phase. This strategy permits concurrent optimization of the total trajectory duration, individual phase trajectories, and phase transition time. The efficacy of the proposed method is validated through two simulations. The first explores a scenario with phase transition, and the second generates a trajectory relying solely on the approach phase. The results affirm our algorithm's effectiveness in deciding transition necessity, identifying optimal transition timing, and optimizing the trajectory accordingly. The proposed two-phase TPBVP approach holds significant implications for advancements in autonomous ship navigation, enhancing safety and efficiency in berthing operations.

• 동력기계공학회지
• /
• 제10권4호
• /
• pp.139-146
• /
• 2006

In this paper vector code correlation(VCC) method and an algorithm to promote the image processing performance in building an effective measurement system using cameras are described for automatically berthing and controlling the ship equipped with side thrusters. In order to realize automatic ship berthing, it is indispensable that the berthing assistant system on the ship should continuously trace a target in the berth to measure the distance to the target and the ship attitude, such that we can make the ship move to the specified location. The considered system is made up of 4 apparatuses compounded from a CCD camera, a camera direction controller, a popular PC with a built in image processing board and a signal conversion unit connected to parallel port of the PC. The object of this paper is to reduce the image processing time so that the berthing system is able to ensure the safety schedule against risks during approaching to the berth. It could be achieved by composing the vector code image to utilize the gradient of an approximated plane found with the brightness of pixels forming a certain region in an image and verifying the effectiveness on a commonly used PC. From experimental results, it is clear that the proposed method can be applied to the measurement system for automatic ship berthing and has the image processing time of fourfold as compared with the typical template matching method.

• 한국항해항만학회지
• /
• 제32권8호
• /
• pp.589-596
• /
• 2008

선박의 접안운동을 자동화하기 위하여 인공신경망(Artificial Neural Network, 이하 ANN)에 의한 제어를 수행하였다. ANN은 시스템의 비선형성이 표현 가능하므로 접안운동과 같은 비선형성이 강한 조종운동에 적합하다. 입력층과 출력층 사이에 하나 이상의 중간층이 존재하는 다층 인식자(Multi-layer perceptron)를 사용하였고, 교사 데이터(Teaching data)와 역전파(Back-Propagation) 알고리즘을 사용하여 신경망의 출력값과 목표 출력값 사이의 오차가 최소가 되도록 신경망 학습을 수행하였다. 접안 시 저속조종 수학모델을 사용하여 접안 시뮬레이션을 수행하였으며, ANN의 입력층 성분(unit)이 8개인 구조와 6개인 구조의 접안 제어를 비교하였다. 시뮬레이션 결과, 두 ANN에 의하여 접안 경로 선택에 차이가 나타났으나 접안 조건은 모두 만족하였다.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 1994년도 춘계학술발표회
• /
• pp.55-67
• /
• 1994

Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics ar low speed. In this paper the authors propose a new berthing control system which can evaluate as closely as captain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's decision-making by using the FNN(Fuzzy neural Network) controller which can simulate captain's knowledge. This berthing controller consists of the navigation subsystem FNN controller and the berthing subsystem FNN controller. The learning data are drawn from Ship Handling Simulator (NavSim NMS90 MK III) and represent the ship motion characteristics internally According to learning procedure both FNN controllers can tune membership functions and identify fuzzy control rules automatically The verified results show the FNN controllers effective to incorporate captain's knowledge and experience of berthing.

• 한국항해항만학회지
• /
• 제27권6호
• /
• pp.625-630
• /
• 2003

In order to keep the safety of maneuverability under the lateral berthing, it is necessary to estimate the magnitudes and properties of the hydrodynamic forces acting on ship hull quantitatively. In this paper, CFD technique is used to calculate the steady lateral force according to the water depth for Wigley model under the unsteady lateral berthing. The numerical results are analysed into the steady lateral force and the transitional lateral force, and some of reviews for the safety of maneuverability relating to the lateral berthing are discussed based on the computed hydrodynamic forces.

• 산업공학
• /
• 제11권1호
• /
• pp.97-103
• /
• 1998

In these days many people have studied on the berthing problem. The operation rules differ from port so port and the problem is highly dependent on the environment of port. The purpose of this study is to develop a decision support system decision makers of the berthing problem for Inchon Port. The system is developed with graphic user interface(GUI) using user-interactive approach and some general and specific rules for Inchon Prot are considered. The system is composed of the following four parts ; the input/output part, the automatic berthing part by the system using rules, the manual berthing part by user, and the part for modifying results or handling exceptional events. The system is designed to assign ship to berths by matching the characteristics with environmental and operational constraints of Inchon Port. We expect that this system can provide decision makers with an efficient and fast way to berthing and can reduce wastes of time, space, and manpower in port operations.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 2006년도 춘계학술대회 및 창립 30주년 심포지엄(논문집)
• /
• pp.67-74
• /
• 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.

• 동력기계공학회지
• /
• 제22권6호
• /
• pp.20-27
• /
• 2018

Vessel maneuvering problem in the harbor area is generating considerable interests in terms of marine cybernetics. In this sense, the vessel is operated and moves at ultimately low or zero speed in shallow water area. So the vessel is usually aided by the cooperation with thrusters, main propulsion system, tugboats and pilots, etc. In this paper, we suggest a new vessel berthing technique using dampers and winches as a solution for excessively complicate and dangerous berthing work. In the proposed berthing method, in order to manipulate the actuators (winches and dampers), a simple and heuristic control strategy is applied for a basic experiment. Finally, experiments are conducted to verify the effectiveness of the proposed automatic vessel berthing strategy based on the heuristic control method.

• International Journal of Naval Architecture and Ocean Engineering
• /
• 제10권3호
• /
• pp.235-249
• /
• 2018

The Artificial Neural Network (ANN) model has been known as one of the most effective theories for automatic ship berthing, as it has learning ability and mimics the actions of the human brain when performing the stages of ship berthing. However, existing ANN controllers can only bring a ship into a berth in a certain port, where the inputs of the ANN are the same as those of the teaching data. This means that those ANN controllers must be retrained when the ship arrives to a new port, which is time-consuming and costly. In this research, by using the head-up coordinate system, which includes the relative bearing and distance from the ship to the berth, a novel ANN controller is proposed to automatically control the ship into the berth in different ports without retraining the ANN structure. Numerical simulations were performed to verify the effectiveness of the proposed controller. First, teaching data were created in the original port to train the neural network; then, the controller was tested for automatic berthing in other ports, where the initial conditions of the inputs in the head-up coordinate system were similar to those of the teaching data in the original port. The results showed that the proposed controller has good performance for ship berthing in ports.