A neural network model for a 5-thruster unmanned underwater vehicle

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

IEEE Region 10 Annual International Conference, Proceedings/TENCON

Publication Date

12-1-2012

Abstract

Unmanned underwater vehicles (UUVs) are mostly used for safe underwater explorations and researches. UUVs are subject to different parameters that changes over time. Such parameters are not considered in kinematic modelling of vehicles. As such, a dynamic modelling of underwater vehicles is necessary. This study proposes a dynamic model that is utilizing Artificial Neural Network (ANN), for a 5-thruster underwater vehicle design. The training data for the ANN model is gathered by empirical methods. The dynamic model is represented by UUV variables: thrusters input voltages and resulting velocity vector. The results of the neural network showed accuracy and reliability due to the low Mean Square Error (MSE) and satisfactory regression plots. © 2012 IEEE.

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Digitial Object Identifier (DOI)

10.1109/TENCON.2012.6412181

Disciplines

Electrical and Computer Engineering | Electrical and Electronics | Systems and Communications

Keywords

Autonomous underwater vehicles; Intelligent agents (Computer software); Neural networks (Computer science)

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