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Pregled bibliografske jedinice broj: 122981

Neural Network based ship steering


Beroš, Slobodan; Markovina, Roko
Neural Network based ship steering // International Maritime Association of the Mediteranean 2002-proceings / S.A. Mavrakos and K.Spyroy (ur.).
Rethymno, Kreta, Grčka: Helenic Institute of Marine Technology, 2002. str. 57-60 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Neural Network based ship steering

Autori
Beroš, Slobodan ; Markovina, Roko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
International Maritime Association of the Mediteranean 2002-proceings / S.A. Mavrakos and K.Spyroy - Rethymno, Kreta, Grčka : Helenic Institute of Marine Technology, 2002, 57-60

Skup
10th International Congress of the International Maritime Association of the Mediteranean 2002

Mjesto i datum
Rethymno, 13. - 17. 05. 2002

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Neural network; automatic ship steering; reduction in cruising time and propulsion power; sea conditions

Sažetak
The automatic ship steering is very important in shipping and shipbuilding industry, either on the clasical sea-going liner ships or on the super-high speed liners - the ships of new generation. The main goals of automatic ship steering, by computer based autopilots, are reduction in cruising times and propulsion power. But, disadvantages of this solution are nonlinear nature of the problem cause of changing the ship's characteristics and/or the sea conditions. In this paper the neural network (NN) models and controllers are proposed and presented, which give the new more precise ship model and open way for successful control once and the model of the real ship is available after learning process. If the model is an accurate representation of the real ship and the controller has been designed correctly, then the controller will work on the real ship. Both of these tasks can be completed using neural network (NN) trained with backpropagation, a common network training technique. The network will be trained to predict the next state of the system given its present state and inputs. After learning time the ship will be steered like &laquo ; ; sitting by the Nellie&raquo ; ; method. The application of this neural network (NN) based ship steering, particurarly on the liners ships would be very usefull and profitable.

Izvorni jezik
Engleski

Znanstvena područja
Brodogradnja, Elektrotehnika



POVEZANOST RADA


Projekt / tema
0023016
0023029

Ustanove
Fakultet elektrotehnike, strojarstva i brodogradnje, Split