Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Application Research of Network Learning Algorithm Based on Neural Network Disturbance Compensation in Satellite Attitude Control

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. Preprints 2021, 2021100436 (doi: 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 (doi: 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

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