Selected Method Of Artificial Intelligence In
Modelling Safe Movement Of Ships
Author(s)
J. Malecki
Abstract
The main goal in this paper is presented using one of the methods of artificial
intelligence, especially neural networks, for determination of the coefficients of
state equations of a ship’s safe motion in a horizontal plane. The recurrent
optimization network is used to identify parameters of the ship’s dynamics. A
structure and the operating principle of the network and results of computer
simulation of a ship’s motion along a desired trajectory are presented in this
paper as simulation trials using the MATLAB program.
Keywords: safe motion, neural network.
1 Introduction
The main problem of ship exploitation in sea movement is assuring the right
level of navigational safety to a ship. In order to increase the reliability level of
sea traffic and the development of its steering, standards have been created [3, 5].
The structure of an automatic safe system of steering a ship must always include
an accurate mathematical model of a ship. Many theoretical and practical works
have been focused on problems of mathematical modelling and methods of
parametric identification were developed especially for safe motion of ships.
These methods were very efficient for both linear static and dynamic objects.
Recently, an increasing interest has been observed in combining artificial
intelligence tools with classical control techniques. Hence neural networks are
used to mathematical model a ship’s dynamic. One of the most important tasks
during designing of safe automatic control systems is defining an accurate
mathematical model of the ship. The results of much research allows one to
model both the linear static and dynamic objects. However, a ship as an
Keywords
safe motion, neural network.
Related Book
Other papers in this volume
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