Proceedings of the 2016 International Conference on Computational Science and Engineering (ICCSE 2016)

Research on Control Model of Flexible Manipulator for Ships Based on Fuzzy Neural Network

Authors
Libo Yang
Corresponding Author
Libo Yang
Available Online October 2016.
DOI
https://doi.org/10.2991/iccse-16.2016.2How to use a DOI?
Keywords
Neural network algorithm, Flexible manipulator, Fuzzy control
Abstract

In this paper, it makes study on a kind of control model of flexible manipulator for ships based on neural network algorithm, this model can solve the operation control problem of flexible manipulator when ships are in the voyage through the combination of traditional fuzzy theory and neural network algorithm. Through simulation, it can verify that this plan can have better effect when it transports the same quality load, which is better suited to dry cargo shipping task when ships are in sailing. At the same time, it can verify the feasibility of the neural network algorithm for the control of flexible manipulator.

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 International Conference on Computational Science and Engineering (ICCSE 2016)
Series
Advances in Computer Science Research
Publication Date
October 2016
ISBN
978-94-6252-239-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/iccse-16.2016.2How 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  - Libo Yang
PY  - 2016/10
DA  - 2016/10
TI  - Research on Control Model of Flexible Manipulator for Ships Based on Fuzzy Neural Network
BT  - Proceedings of the 2016 International Conference on Computational Science and Engineering (ICCSE 2016)
PB  - Atlantis Press
SP  - 9
EP  - 13
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-16.2016.2
DO  - https://doi.org/10.2991/iccse-16.2016.2
ID  - Yang2016/10
ER  -