✦ LIBER ✦

Dynamic model of manoeuvrability using recursive neural networks

✍ Scribed by L. Moreira; C. Guedes Soares

Publisher: Elsevier Science
Year: 2003
Tongue: English
Weight: 433 KB
Volume: 30
Category: Article
ISSN: 0029-8018
DOI: 10.1016/s0029-8018(02)00147-6

No coin nor oath required. For personal study only.

✦ Synopsis

This paper presents a Recursive Neural Network (RNN) manoeuvring simulation model for surface ships. Inputs to the simulation are the orders of rudder angle and ship's speed and also the recursive outputs velocities of sway and yaw. This model is used to test the capabilities of artificial neural networks in manoeuvring simulation of ships. Two manoeuvres are simulated: tactical circles and zigzags. The results between both simulations are compared in order to analyse the accuracy of the RNN. The simulations are performed for the Mariner hull. The data generated to train the network are obtained from a manoeuvrability model performing the simulation of different manoeuvring tests. The RNN proved to be a robust and accurate tool for manoeuvring simulation.

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