Open AccessArtificial Neural Network Controller for Automatic Ship Berthing Using Separate Route
Author(s) -
Qiang Li,
Hong Bao
Publication year - 2020
Publication title -
journal of web engineering/journal of web engineering on line
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.151
H-Index - 13
eISSN - 1544-5976
pISSN - 1540-9589
DOI - 10.13052/jwe1540-9589.19788
Subject(s) - rudder , artificial neural network , port (circuit theory) , computer science , process (computing) , controller (irrigation) , marine engineering , simulation , artificial intelligence , engineering , agronomy , electrical engineering , biology , operating system
The operation of ships in the port area requires not only the assistance of in-vessel equipment such as main engines and rudder, but also the assistance of external equipment such as tugboats. The complexity in the operation of ships in the port, requires control algorithm with multiple input and output for the automatic berthing control of the ship. The entering and leaving data of the ship can help the algorithm to efficiently control the berthing and un-berthing process of ships. This is based on the artificial intelligence which has been continuously approaching the operating habits of the pilot. The advances in artificial intelligence can control the entering, turning, and berthing in the port by artificial intelligence. In this study, the artificial neural network algorithm has been used to establish an automatic berthing model, based on the scheduled route. With the help of training data of one port, this model can be applied to the ship’s berthing with different berth layouts. Furthermore, it can also be applied to complex systems such as direct or turning-berthing of a ship. Finally, the automatic berthing model has been used for the simulation of direct berthing and turning-berthing in different berth.