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
Recommended Citation
Simbulan, K., David, K., Vicerra, R. P., Atienza, R., & Dadios, E. P. (2012). A neural network model for a 5-thruster unmanned underwater vehicle. IEEE Region 10 Annual International Conference, Proceedings/TENCON https://doi.org/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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