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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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Published in: | Computational intelligence and neuroscience 2022-08, Vol.2022, p.1-13 |
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description | 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. |
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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.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2022/8289934</identifier><identifier>PMID: 36110911</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>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</subject><ispartof>Computational intelligence and neuroscience, 2022-08, Vol.2022, p.1-13</ispartof><rights>Copyright © 2022 Wenjing Pei.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>Copyright © 2022 Wenjing Pei. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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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.</description><subject>Algorithms</subject><subject>Cameras</subject><subject>Context</subject><subject>Control theory</subject><subject>Controllers</subject><subject>Data mining</subject><subject>Fuzzy control</subject><subject>Fuzzy logic</subject><subject>Hyperbolic functions</subject><subject>Information processing</subject><subject>Laws, regulations and rules</subject><subject>Machine learning</subject><subject>Satellite attitude control</subject><subject>Satellite imagery</subject><subject>Satellite tracking</subject><subject>Satellites</subject><subject>Sliding mode control</subject><subject>Spacetime</subject><subject>Spatial discrimination learning</subject><subject>Tracking 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Imaging Attitude Tracking Control Laws for Video Satellites Based on Image Information by Hyperbolic Tangent Fuzzy Sliding Mode Control</title><author>Pei, Wenjing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c383t-3c5d97a579a8fb8f7958717a12f0b7a10b3e0fc673dc3a942d094ecd26cfebb53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Cameras</topic><topic>Context</topic><topic>Control theory</topic><topic>Controllers</topic><topic>Data mining</topic><topic>Fuzzy control</topic><topic>Fuzzy logic</topic><topic>Hyperbolic functions</topic><topic>Information processing</topic><topic>Laws, regulations and rules</topic><topic>Machine learning</topic><topic>Satellite attitude control</topic><topic>Satellite imagery</topic><topic>Satellite tracking</topic><topic>Satellites</topic><topic>Sliding mode control</topic><topic>Spacetime</topic><topic>Spatial 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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.</abstract><cop>New York</cop><pub>Hindawi</pub><pmid>36110911</pmid><doi>10.1155/2022/8289934</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-0502-6117</orcidid><oa>free_for_read</oa></addata></record> |
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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 |
title | Staring Imaging Attitude Tracking Control Laws for Video Satellites Based on Image Information by Hyperbolic Tangent Fuzzy Sliding Mode Control |
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