@inproceedings{ab21cf9fd9b2455493467b7710055f8e,
title = "RBFNN-based sliding mode control for flexible spacecraft vibration suppress",
abstract = "Vibration suppress of a flexible spacecraft during attitude maneuvering is a challenging task. In this paper, the proposed control includes two major parts: command profile is designed to maneuver a flexible spacecraft with very little residual vibration and an intelligent control scheme consists of an online radial basis function neural network(RBFNN) based slide mode control is performed such that improved tracking accuracy is accomplished in the presence of parametric uncertainties. The input shape is designed to modify the command for elimination of the residual vibration in the open loop, and an RBF neural network based slide mode control law is proposed to achieve system stability and good performance in the closed-loop. With the proposed control law, simulation results verified that the control scheme can achieve the maneuver with high accuracy of little residual vibration.",
keywords = "Flexible spacecraft, Input shape, RBFNN, Slide mode",
author = "Qiang Tang and Yan Wang and Yongjun Lei and Xinglin Chen",
year = "2009",
doi = "10.1109/IITA.2009.321",
language = "英语",
isbn = "9780769538594",
series = "3rd International Symposium on Intelligent Information Technology Application, IITA 2009",
pages = "194--197",
booktitle = "3rd International Symposium on Intelligent Information Technology Application, IITA 2009",
note = "3rd International Symposium on Intelligent Information Technology Application, IITA 2009 ; Conference date: 21-11-2009 Through 22-11-2009",
}