Neural network-based distributed adaptive attitude synchronization control of spacecraft formation under modified fast terminal sliding mode

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• 作者：Lin Zhao^a ; ^{zhaolin1585@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Yingmin Jia^a ; ^b ; ^{ymjia@buaa.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Spacecraft formation flying (SFF) ; Attitude synchronization ; Terminal sliding mode (TSM) ; Neural network (NN) ; Input constraint
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：1 January 2016
• 年：2016
• 卷：171
• 期：Complete
• 页码：230-241
• 全文大小：1294 K

文摘

This paper investigates the distributed attitude synchronization control of spacecraft formation flying (SFF) in the presence of unknown external disturbances. A novel multi-spacecraft modified fast terminal sliding mode (MFTSM) is designed, which not only avoids the singularity problem, but also contains the advantages of fast terminal sliding mode (FTSM). Based on the MFTSM and neutral network (NN) approximation techniques, a distributed MFTSM control law with adaptive tuning law is proposed. Moreover, a distributed MFTSM control law considering input constraint is also given. Both the two control laws can guarantee the attitude tracking errors that converge to the regions containing the origin in finite time and are independent on the precise knowledge of inertia matrix. Simulation results are presented to demonstrate the effectiveness of designed schemes.