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http://dx.doi.org/10.5394/KINPR.2008.32.8.589

A Study of the Automatic Berthing System of a Ship Using Artificial Neural Network  

Bae, Cheol-Han (Graduate school of Department of Naval Architecture and Ocean Engineering Pusan National University)
Lee, Seung-Keon (Department of Naval Architecture and Ocean Engineering Pusan National University)
Lee, Sang-Eui (Department of Naval Architecture and Ocean Engineering Pusan National University)
Kim, Ju-Han (Graduate school of Department of Naval Architecture and Ocean Engineering Pusan National University)
Publication Information
Journal of Navigation and Port Research / v.32, no.8, 2008 , pp. 589-596 More about this Journal
Abstract
In this paper, Artificial Neural Network(ANN) is applied to automatic berthing control for a ship. ANN is suitable for a maneuvering such as ship's berthing, because it can describe non-linearity of the system. Multi-layer perceptron which has more than one hidden layer between input layer and output layer is applied to ANN. Using a back-propagation algorithm with teaching data, we trained ANN to get a minimal error between output value and desired one. For the automatic berthing control of a containership, we introduced low speed maneuvering mathematical models. The berthing control with the structure of 8 input layer units in ANN is compared to 6 input layer units. From the simulation results, the berthing conditions are satisfied, even though the berthing paths are different.
Keywords
Automatic berthing system; Artificial neural network(ANN); Low speed maneuvering mathematical model; Multi-layer perceptron; Back-propagation algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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