Proceedings of the 2016 International Conference on Advanced Materials Science and Environmental Engineering

Fuzzy Logic Controller for Enhancing RCS's Lab Measurements

Authors
Mohamed Galal, Jianyu Wang
Corresponding Author
Mohamed Galal
Available Online April 2016.
DOI
https://doi.org/10.2991/amsee-16.2016.63How to use a DOI?
Keywords
RCS lab measurements enhancement; fuzzy logic control; multi-input and multi output; nonlinear system; and video guidance
Abstract

Precise and accurate radar cross section (RCS) measurements, especially for tracking small radar cross section targets (e.g. tracks on Fighters), or RCS reduction and radar absorbing materails evaluation for other targets of interest such as aircraft, tanks, or ships, is a must. As a consequence, the need of having more accurate evaluation for the RCS of the targets is required. This paper demonstrates the existing RCS's Lab. Then, discusses the automation of the RCS's antenna holder movements, using fuzzy logic, to have better target tracking while measurement process, in order to suppress the unwanted manmade error. Taking into account the fuzzy nature of human decision making processes and real-time properties, this paper has established different fuzzy controllers then tested and compared with a crisp decision system. The first one has been developed using an expert knowledge, the second one was learned from the recorded videos.

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 Advanced Materials Science and Environmental Engineering
Series
Advances in Engineering Research
Publication Date
April 2016
ISBN
10.2991/amsee-16.2016.63
ISSN
2352-5401
DOI
https://doi.org/10.2991/amsee-16.2016.63How 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  - Mohamed Galal
AU  - Jianyu Wang
PY  - 2016/04
DA  - 2016/04
TI  - Fuzzy Logic Controller for Enhancing RCS's Lab Measurements
BT  - Proceedings of the 2016 International Conference on Advanced Materials Science and Environmental Engineering
PB  - Atlantis Press
SP  - 236
EP  - 240
SN  - 2352-5401
UR  - https://doi.org/10.2991/amsee-16.2016.63
DO  - https://doi.org/10.2991/amsee-16.2016.63
ID  - Galal2016/04
ER  -