An Application of ANN to Automatic Ship Berthing Using Selective Controller

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.