Adaptive neural' network-based satellite attitude control in the presence of CMG uncertainty

被引：41

作者：

MacKunis, W. ^{[1
]}

Leve, F. ^{[2
]}

Patre, P. M. ^{[3
]}

Fitz-Coy, N. ^{[4
]}

Dixon, W. E. ^{[4
]}

机构：

[1] Embry Riddle Aeronaut Univ, Dept Phys Sci, Daytona Beach, FL 32114 USA

[2] Kirtland Air Force Base, Air Force Res Lab, Albuquerque, NM 87117 USA

[3] TE Connect, Adv Mfg Technol Sect, Harrisburg, PA 17111 USA

[4] Univ Florida, Dept Mech & Aerosp Engn, Gainesville, FL 32611 USA

来源：

AEROSPACE SCIENCE AND TECHNOLOGY | 2016年 / 54卷

关键词：

MANIPULATORS; VELOCITY; INERTIA;

D O I：

10.1016/j.ast.2016.04.022

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

An attitude tracking controller is developed for control moment gyroscope (CMG)-actuated satellites, which is shown to achieve accurate attitude tracking in the presence of unmodeled external disturbance torques, parametric uncertainty, and nonlinear CMG disturbances. Since the disturbances/uncertainties do not all satisfy the typical linear-in-the-parameters (LP) assumption, a neural network (NN) is included in the control development. The innovation of the result is the development of a Lyapunov-based design/analysis that indicates exponential convergence to an arbitrarily small domain. The result is obtained despite the characteristics of the uncertainty; the nonvanishing disturbance terms; and the fact that the control input is premultiplied by a non-square, time-varying, nonlinear, uncertain matrix. In addition to the Lyapunov-based analysis, experimental results demonstrate the performance of the developed controller. (C) 2016 Elsevier Masson SAS. All rights reserved.

引用

页码：218 / 228

页数：11

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