Title :
Attitude synchronization of spacecraft formation using neural network
Author :
Min, Haibo ; Sun, Fuchun ; Wang, Shicheng ; Zhang, Jinsheng ; Gao, Zhijie
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Abstract :
We address the problem of high-precision attitude synchronization in a leader-follower spacecraft formation architecture using robust integral of the sign of the error (RISE) based Neural Network (NN) technique. Based on the relative attitude dynamic model of the spacecraft formation, RISE is introduced to approximate the dynamics of the follower as well as various external disturbances. It is shown that the errors of the entire formation closed-loop are Asymptotical Stable (AS), which possesses significant advantage over the typical Uniformly Upper Bounded (UUB) property of most NN controllers in high-precision attitude synchronization tasks. Numerical simulation is provided to illustrate the effectiveness of the proposed algorithm.
Keywords :
aircraft; approximation theory; asymptotic stability; attitude control; closed loop systems; multi-agent systems; neural nets; pattern formation; synchronisation; asymptotic stable; attitude dynamic model; attitude synchronization; follower dynamics approximation; neural network; robust integral; spacecraft formation; uniformly upper bounded property; Approximation methods; Artificial neural networks; Chromium; Lead; Space vehicles; Stability analysis; Synchronization;
Conference_Titel :
Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8041-8
DOI :
10.1109/COGINF.2010.5599764
