A Self-learning Control Strategy for Vibration Isolated Control Moment Gyroscope

被引：0

作者：

Lai, Lin ^{[1
]}

Lu, Ming ^{[1
]}

Zhang, Jiyang ^{[1
]}

Zhang, Qiang ^{[1
]}

Li, Gang ^{[1
]}

机构：

[1] Beijing Inst Control Engn, Beijing Key Lab Long Life Technol Precise Rotat &, Beijing 100190, Peoples R China

来源：

2020 CHINESE AUTOMATION CONGRESS (CAC 2020) | 2020年

关键词：

CMG; self-learning; vibration isolator;

D O I：

10.1109/CAC51589.2020.9327770

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to improve the imaging resolution of remote sensing satellites, one effective method is to isolate the vibration generated by the onboard Control Moment Gyroscope (CMG). However, vibration isolators have severe impact on the system model of CMGs, which significantly degrade its performance on attitude controL In this paper, a nonlinear virtual control object model based on neural network and a self-learning compensation controller are integrated in the original control scheme to achieve strong robust control for the system. The control performance of this strategy is verified by experiments on a real CMG system.

引用

页码：4965 / 4968

页数：4

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