Corrections to “Finite-Time Attitude Tracking Control for Spacecraft Using Terminal Sliding Model and Chebyshev Neural Network”

2013 ◽  
Vol 43 (2) ◽  
pp. 803-803 ◽  
Author(s):  
An-Min Zou ◽  
Krishna Dev Kumar ◽  
Zeng-Guang Hou
Keyword(s):  
Neural Network ◽  
Finite Time ◽  
Tracking Control ◽  
Chebyshev Neural Network ◽  
Attitude Tracking ◽  
Attitude Tracking Control

Active attitude fault-tolerant tracking control of flexible spacecraft via the Chebyshev neural network

2018 ◽  
Vol 41 (4) ◽  
pp. 925-933 ◽  
Author(s):  
Kunfeng Lu ◽  
Tianya Li ◽  
Lijun Zhang
Keyword(s):  
Neural Network ◽  
Finite Time ◽  
Tracking Control ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Flexible Spacecraft ◽  
Control Law ◽  
Chebyshev Neural Network ◽  
Uncertain Dynamics ◽  
Attitude Tracking

This paper describes a novel finite-time attitude tracking control approach for flexible spacecraft. This is achieved by integrating sliding-mode control and the active real-time fault-tolerant reconfiguration method. In this approach, the attitude error dynamics and the kinematics of the flexible spacecraft are first established. Then, a nonsingular terminal sliding-mode surface is designed, based on finite-time control theory. Applying the Chebyshev neural network, the uncertain dynamics induced by external disturbances and uncertain inertia parameters are approximated and estimated. The nominal control law and the compensation control law to obtain the active reconfiguration fault-tolerant controller are finally developed in normal and fault conditions, respectively. The closed-loop tracking system is proved to be uniformly ultimately bounded stable after a finite time. Numerical simulations are presented for a flexible spacecraft to illustrate the efficiency of the proposed controller.

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