Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering

Adaptive Course Control System of an Unmanned Surface Vehicle (USV) Based on Back-propagation Neural Network (BPNN)

Authors
Yang Fang, Huajun Zhang, Biao Wang, Chaochao Jiang
Corresponding Author
Yang Fang
Available Online October 2016.
DOI
10.2991/mmme-16.2016.175How to use a DOI?
Keywords
adaptive course control system; USV; back-propagation neural network; stochastic optimization
Abstract

Unmanned Surface Vehicle (USV) is a small surface naval vessel which navigates and plans by itself. And undoubtedly, it plays a vital role in now and future naval battle and sea rescue. Adaptive course control is a necessary part of USV control, and in recent years, many researchers have done plenty of works on it, howev-er, many of their method did not solve the problem of the accuracy of transfer function or did not solve course maneuvering problems in a simple and efficient way. In view of this problem, we propose a novel adap-tive course control method based on back-propagation neural network (BPNN), PID (proportional, integral, derivative) algorithm and stochastic optimization. The method uses model reference adaptive theory and PID algorithm combined together to minimize the course error. And stochastic optimization is also utilized for weight adjustment of neural network. In this way, the system can output rudder angle efficiently and accu-rately in order to achieve course control of USV. Simulation results showed that the proposed method has great efficiency and theoretical feasibility and its response time is very short.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
978-94-6252-221-3
ISSN
2352-5401
DOI
10.2991/mmme-16.2016.175How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yang Fang
AU  - Huajun Zhang
AU  - Biao Wang
AU  - Chaochao Jiang
PY  - 2016/10
DA  - 2016/10
TI  - Adaptive Course Control System of an Unmanned Surface Vehicle (USV) Based on Back-propagation Neural Network (BPNN)
BT  - Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
PB  - Atlantis Press
SP  - 732
EP  - 735
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmme-16.2016.175
DO  - 10.2991/mmme-16.2016.175
ID  - Fang2016/10
ER  -