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2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7




ISSN 2083-6473
ISSN 2083-6481 (electronic version)




Associate Editor
Prof. Tomasz Neumann

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
An Application of ANN to Automatic Ship Berthing Using Selective Controller
1 Mokpo National Maritime University, Mokpo, South Korea
2 Pusan National University, Pusan, South Korea
ABSTRACT: This paper deals with ANN(Artificial Neural Networks) and its application to automatic ship berthing. As ship motions are expressed by a multi-term non-linear model, it is very difficult to find optimal methods for automatic ship berthing. When a ship makes its berthing operation, the ship's inertia and slow motion make the ship approach to final berthing point with pre-determined navigation pattern. If the ship is out of the pre-determined navigation pattern, the berthing usually end in failure. It has been known that the automatic control for ship's berthing cannot cope with various berthing situations such as various port shape and approaching directions. For these reasons, the study on automatic berthing using ANN usually have been carried out based on one port shape and predetermined approaching direction. In this paper, new algorithm with ANN controller was suggested to cope with these problems. Under newly suggested algorithm, the controller can select different weight on the link of neural networks according to various situations, so the ship can maintain stable berthing operation even in different situations. Numerical simulations are carried out with this control system to find its improvement.
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Citation note:
Im N., Lee S.K., Hyung D.B.: An Application of ANN to Automatic Ship Berthing Using Selective Controller. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 1, No. 1, pp. 101-105, 2007

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