Version 1
: Received: 27 October 2021 / Approved: 28 October 2021 / Online: 28 October 2021 (12:44:22 CEST)
How to cite:
Leo John, F.; Dogra, D. Application Research of Network Learning Algorithm Based on Neural Network Disturbance Compensation in Satellite Attitude Control. Preprints2021, 2021100436. https://doi.org/10.20944/preprints202110.0436.v1
Leo John, F.; Dogra, D. Application Research of Network Learning Algorithm Based on Neural Network Disturbance Compensation in Satellite Attitude Control. Preprints 2021, 2021100436. https://doi.org/10.20944/preprints202110.0436.v1
Leo John, F.; Dogra, D. Application Research of Network Learning Algorithm Based on Neural Network Disturbance Compensation in Satellite Attitude Control. Preprints2021, 2021100436. https://doi.org/10.20944/preprints202110.0436.v1
APA Style
Leo John, F., & Dogra, D. (2021). Application Research of Network Learning Algorithm Based on Neural Network Disturbance Compensation in Satellite Attitude Control. Preprints. https://doi.org/10.20944/preprints202110.0436.v1
Chicago/Turabian Style
Leo John, F. and Deeksha Dogra. 2021 "Application Research of Network Learning Algorithm Based on Neural Network Disturbance Compensation in Satellite Attitude Control" Preprints. https://doi.org/10.20944/preprints202110.0436.v1
Abstract
Based on the satellite attitude control method, this paper proposes an attitude control method based on neural network disturbance compensation. The paper firstly analyzes the neural network algorithm and proposes an orthogonal least squares algorithm to implement network learning. In this paper, a set of high-precision directional neural network compensation controllers is designed for the attitude control of acupuncture small satellites. The feasibility of the improved orthogonal least-squared algorithm combined with the neural network supplementary control method in satellite attitude control is verified by experiments.
Keywords
orthogonal least squares algorithm; neural network; disturbance compensation; satellite atti-tude control
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.