@inproceedings{6d52563bb1f743b0936ae41718ba4608,
title = "Chebyshev neural network-based finite-time sliding mode control of spacecraft formation",
abstract = "The problem of finite time control of spacecraft formation is investigated in this paper. A nonsingular fast terminal sliding mode (NFTSM) control scheme is proposed by using Chebyshev Neural Network (CNN) for spacecraft formation. A nonsingular fast terminal sliding mode (NFTSM) control strategy is designed for spacecraft formation flying. In order to approximate the desired nonlinear function and external disturbances a CNN is employed. In addition, finite-time convergence nature of controller is proved by using Lyapunov stability theory. Finally, numerical simulations demonstrate the effectiveness and feasibility of the proposed controller.",
keywords = "Neural Networks, Nonsingular Fast Terminal Sliding Mode, Spacecraft Formation Flying",
author = "Ruixia Liu and Ming Liu and Dong Ye and Lei Xing",
note = "Publisher Copyright: {\textcopyright} 2017 Technical Committee on Control Theory, CAA.; 36th Chinese Control Conference, CCC 2017 ; Conference date: 26-07-2017 Through 28-07-2017",
year = "2017",
month = sep,
day = "7",
doi = "10.23919/ChiCC.2017.8028598",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "7852--7856",
editor = "Tao Liu and Qianchuan Zhao",
booktitle = "Proceedings of the 36th Chinese Control Conference, CCC 2017",
address = "美国",
}