Staring Imaging Attitude Tracking Control Laws for Video Satellites Based on Image Information by Hyperbolic Tangent Fuzzy Sliding Mode Control

This paper studies the staring imaging attitude tracking and control for satellite videos based on image information. An improved temporal-spatial context learning algorithm is employed to extract the image information. Based on this, a hyperbolic tangent fuzzy sliding mode control law is proposed t...

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Bibliographic Details
Published in:Computational intelligence and neuroscience 2022-08, Vol.2022, p.1-13
Main Author: Pei, Wenjing
Format: Article
Language:English
Subjects:
Algorithms
Cameras
Context
Control theory
Controllers
Data mining
Fuzzy control
Fuzzy logic
Hyperbolic functions
Information processing
Laws, regulations and rules
Machine learning
Satellite attitude control
Satellite imagery
Satellite tracking
Satellites
Sliding mode control
Spacetime
Spatial discrimination learning
Tracking control
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Summary:This paper studies the staring imaging attitude tracking and control for satellite videos based on image information. An improved temporal-spatial context learning algorithm is employed to extract the image information. Based on this, a hyperbolic tangent fuzzy sliding mode control law is proposed to achieve the attitude tracking and control. Furthermore, the hyperbolic tangent function and fuzzy logic system are introduced into the sliding mode controller. In the experiments, the improved temporal-spatial context learning algorithm is applied for the image information of the space target video sequence captured by Jilin-1 in orbit, where the image information is used as the input of the control loop. Moreover, the proposed method is realized through simulation. Besides, the image change caused by attitude adjustment is achieved successfully, and the target imaging can be located in the center of the image plane to realize the gaze tracking control of the space target effectively.
ISSN:1687-5265
1687-5273
DOI:10.1155/2022/8289934