DocumentCode :
2864431
Title :
Shape Estimation of Inflatable Space Structures Using Radial Basis Function Neural Networks
Author :
Peng, Fujun ; Hu, Yan-Ru ; Ng, Alfred
Author_Institution :
Directorate of Spacecraft Eng., Canadian Space Agency, St. Hubert, Que.
fYear :
2006
fDate :
25-28 June 2006
Firstpage :
222
Lastpage :
227
Abstract :
Inflatable space structures need to maintain in a desired shape in space in order to achieve satisfactory performance. The active shape control technique has shown its advantages in solving this problem. One difficulty to realize an active control system in space is how to measure the shape of inflatable structures. This paper proposes a neural network scheme to estimate the shape of inflatable structures, instead of performing measurements directly. A radial basis function neural network is trained on the ground to map environment information and control variables into the structure shape. After the neural network training completes, an estimation of the structure shape can be obtained by inputting the measured environment data and control variables to the neural network. Some validation studies have been conducted in laboratory on the estimation of the flatness of a rectangular Kapton membrane. The results showed the proposed scheme gave very good estimations of the membrane flatness
Keywords :
aerospace engineering; radial basis function networks; shape control; active shape control technique; inflatable space structures; neural network scheme; radial basis function neural networks; rectangular Kapton membrane; shape estimation; Biomembranes; Control systems; Extraterrestrial measurements; Neural networks; Radial basis function networks; Shape control; Shape measurement; Space vehicles; Synthetic aperture radar; Temperature; RBF neural networks; inflatable space structures; shape control; shape estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference on
Conference_Location :
Luoyang, Henan
Print_ISBN :
1-4244-0465-7
Electronic_ISBN :
1-4244-0466-5
Type :
conf
DOI :
10.1109/ICMA.2006.257500
Filename :
4026084
Link To Document :
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