Particle swarm optimization of neural controller for tanker ship steering

Loo, C. K. and Mastorakis, Nikos E. (2007) Particle swarm optimization of neural controller for tanker ship steering. In: 11th WSEAS International Conference on Circuits, 23-25 JUL 2007, Agios Nikolaos, GREECE.

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Abstract

This paper discussed the implementation of Particle Swarm Optimization (PSO) to optimize a Radial Basis Function (RBF) neural controller for tanker ship control. The RBF neural controller uses reinforcement learning strategy to achieve the heading regulation of tanker ship exposed to plant changes and disturbances. However, the tuning of the neural controller design parameters are considered to be difficult and tedious due to the high nonlinearity of the ship dynamic model and the external disturbances. It is shown that PSO can provide a very promising technique for its simplicity and ease of use. Moreover, Centroidal Voronoi Tessellation (CVT) is implemented to select the starting positions of the particles strategically. The promising results from the experiment provide direct evidence for the feasibility and effectiveness of PSO for the optimization of neural controller for tanker ship heading regulation.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > T Technology (General)
Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 12 Oct 2011 08:12
Last Modified: 12 Oct 2011 08:12
URI: http://shdl.mmu.edu.my/id/eprint/3236

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