Swarm intelligence applied to identification of nonlinear ship steering model

Author

Tomera, Miroslaw

Author_Institution

Dept. of Ship Autom., Gdynia Maritime Univ., Gdynia, Poland

fYear

2015

fDate

24-26 June 2015

Firstpage

133

Lastpage

139

Abstract

The paper presents optimization of parameters of nonlinear dynamic ship steering model with one degree of freedom, in which the input is the commanded rudder angle and the output is the ship course. Optimization of parameters concerned the Bech and Wagner-Smith model for which the nonlinearity was determined from a standard Bech´s reverse spiral test, whilst the parameters describing dynamic properties of the ship were determined based on the Kempf´s zigzag maneuver. Optimal parameters of the searched ship model were found using swarm intelligence algorithms, including: ant colony optimization, artificial bee colony, and particle swarm optimization. Rate tests were conducted to find the optimal solution, and a comparative analysis of the results was made.

Keywords

ant colony optimisation; identification; particle swarm optimisation; ships; steering systems; swarm intelligence; Bech model; Bech reverse spiral test; Kempf zigzag maneuver; Wagner-Smith model; ant colony optimization; artificial bee colony; nonlinear dynamic ship steering model; nonlinear ship steering model identification; parameter optimization; particle swarm optimization; swarm intelligence algorithms; Flowcharts; Marine vehicles; Mathematical model; Optimization; Particle swarm optimization; Spirals; Standards; ant colony algorithm; artificial bee colony algorithm; modelling; nonlinear systems; particle swarm optimization; ship´s dynamics; swarm intelligence;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on

Conference_Location

Gdynia

Print_ISBN

978-1-4799-8320-9

Type

conf

DOI

10.1109/CYBConf.2015.7175920

Filename

7175920