Journal of Navigation and Port Research 2008;32(8):589-596.
Published online October 30, 2008.
인공신경망을 이용한 선박의 자동접안 제어에 관한 연구
배철한, 이승건, 이상의, 김주한
A Study of the Automatic Berthing system of a Ship Using Artificial Neural Network
Cheol-Han Bae, Seung-Keon Lee, Sang-Eui Lee, Ju-Han Kim
Abstract
In this paper, Artificial Neural Network(ANN) ís 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 mínímal 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.
Key Words: Automatic berthing system;Artificial neural network(ANN);Low speed maneuvering mathematical model; Multi-layer perceptron;Back-propagation algorithm


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