Adaptive Neural Network Based on Finite-Time Attitude Control for Rigid Spacecraft during Orbit Maneuver

被引：0

作者：

He, Xin ^{[1
]}

Liang, Weikui ^{[2
]}

Guo, Yanning ^{[1
]}

Li, Chuanjiang ^{[1
]}

机构：

[1] Harbin Inst Technol, Harbin 150001, Heilongjiang, Peoples R China

[2] Aerosp Syst Engn Shanghai, Shanghai 201109, Peoples R China

来源：

2018 37TH CHINESE CONTROL CONFERENCE (CCC) | 2018年

基金：

中国国家自然科学基金;

关键词：

Rigid spacecraft; neural network; finite-time control; STABILIZATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Spacecraft performance of attitude control is influenced by orbit control force during orbit maneuver, and exerts an impact on orbit control. To maintain the stability of the system, an adaptive neural network attitude controller based on finite-time for rigid spacecraft is designed where a neural network is utilized to approximate the general disturbances including the drift of mass center, thruster misalignment, and parameter uncertainties. The finite-time stability of the closed-loop system is demonstrated by finite-time Lyapunov stability theory. Then, the controller is applied to the rigid spacecraft with uncertainties. The results of simulation show the effectiveness of the proposed control law.

引用

页码：3096 / 3101

页数：6

共 14 条

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