Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

Optimization for Deployable Antenna in Condition with Working State

Authors
Guoqiang You
Corresponding Author
Guoqiang You
Available Online April 2017.
DOI
10.2991/emim-17.2017.348How to use a DOI?
Keywords
Optimization; Deployable antenna; Cable tension; Optimum mathematic model; Genetic algorithm
Abstract

In this paper, the structure of a large spaceborn deployable antenna is optimized in condition with its working state. The main aim is to obtain the lightest antenna's weight for lower costs. In the optimization process, the optimum mathematic model is established with outer radius of antenna's beam elements and cable tensions as variables, surface precision and natural frequency as constrains, and antenna's weight as objective. Based on the finite element analysis, a genetic algorithm is used to solve this nonlinear mathematic model. And results of example show that this optimization method can effectively reduce antenna's weight as well as keep antenna's structural properties satisfied.

Copyright
© 2017, 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 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
Series
Advances in Computer Science Research
Publication Date
April 2017
ISBN
978-94-6252-356-2
ISSN
2352-538X
DOI
10.2991/emim-17.2017.348How to use a DOI?
Copyright
© 2017, 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  - Guoqiang You
PY  - 2017/04
DA  - 2017/04
TI  - Optimization for Deployable Antenna in Condition with Working State
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 1712
EP  - 1718
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.348
DO  - 10.2991/emim-17.2017.348
ID  - You2017/04
ER  -