Staring Imaging Real-Time Optimal Control Based on Neural Network

In this paper, a real-time optimal attitude controller is designed for staring imaging, and the output command is based on future prediction. First, the mathematical model of staring imaging is established. Then, the structure of the optimal attitude controller is designed. The controller consists o...

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Main Authors: Peiyun Li, Yunfeng Dong, Hongjue Li
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:International Journal of Aerospace Engineering
Online Access:http://dx.doi.org/10.1155/2020/8822223
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author Peiyun Li
Yunfeng Dong
Hongjue Li
author_facet Peiyun Li
Yunfeng Dong
Hongjue Li
author_sort Peiyun Li
collection DOAJ
description In this paper, a real-time optimal attitude controller is designed for staring imaging, and the output command is based on future prediction. First, the mathematical model of staring imaging is established. Then, the structure of the optimal attitude controller is designed. The controller consists of a preprocessing algorithm and a neural network. Constructing the neural network requires training samples generated by optimization. The objective function in the optimization method takes the future control effect into account. The neural network is trained after sample creation to achieve real-time optimal control. Compared with the PID (proportional-integral-derivative) controller with the best combination of parameters, the neural network controller achieves better attitude pointing accuracy and pointing stability.
format Article
id doaj-art-bf80c7a69e634f9db32c325b62746cd7
institution OA Journals
issn 1687-5966
1687-5974
language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series International Journal of Aerospace Engineering
spelling doaj-art-bf80c7a69e634f9db32c325b62746cd72025-08-20T02:19:26ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742020-01-01202010.1155/2020/88222238822223Staring Imaging Real-Time Optimal Control Based on Neural NetworkPeiyun Li0Yunfeng Dong1Hongjue Li2School of Astronautics, Beihang University, Beijing 100191, ChinaSchool of Astronautics, Beihang University, Beijing 100191, ChinaSchool of Astronautics, Beihang University, Beijing 100191, ChinaIn this paper, a real-time optimal attitude controller is designed for staring imaging, and the output command is based on future prediction. First, the mathematical model of staring imaging is established. Then, the structure of the optimal attitude controller is designed. The controller consists of a preprocessing algorithm and a neural network. Constructing the neural network requires training samples generated by optimization. The objective function in the optimization method takes the future control effect into account. The neural network is trained after sample creation to achieve real-time optimal control. Compared with the PID (proportional-integral-derivative) controller with the best combination of parameters, the neural network controller achieves better attitude pointing accuracy and pointing stability.http://dx.doi.org/10.1155/2020/8822223
spellingShingle Peiyun Li
Yunfeng Dong
Hongjue Li
Staring Imaging Real-Time Optimal Control Based on Neural Network
International Journal of Aerospace Engineering
title Staring Imaging Real-Time Optimal Control Based on Neural Network
title_full Staring Imaging Real-Time Optimal Control Based on Neural Network
title_fullStr Staring Imaging Real-Time Optimal Control Based on Neural Network
title_full_unstemmed Staring Imaging Real-Time Optimal Control Based on Neural Network
title_short Staring Imaging Real-Time Optimal Control Based on Neural Network
title_sort staring imaging real time optimal control based on neural network
url http://dx.doi.org/10.1155/2020/8822223
work_keys_str_mv AT peiyunli staringimagingrealtimeoptimalcontrolbasedonneuralnetwork
AT yunfengdong staringimagingrealtimeoptimalcontrolbasedonneuralnetwork
AT hongjueli staringimagingrealtimeoptimalcontrolbasedonneuralnetwork