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A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements

This paper proposes a novel interconnected observer to get good estimates of attitude and gyro bias from high-noise vector measurements. The observer is derived based on the theory of nonlinear and linear cascade systems, and its error dynamics have the properties of global exponential stability and...

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Detalles Bibliográficos
Autores principales: Guo, Huijuan, Liu, Huiying, Hu, Xiaoxiang, Zhou, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7697328/
https://www.ncbi.nlm.nih.gov/pubmed/33202646
http://dx.doi.org/10.3390/s20226514
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author Guo, Huijuan
Liu, Huiying
Hu, Xiaoxiang
Zhou, Yan
author_facet Guo, Huijuan
Liu, Huiying
Hu, Xiaoxiang
Zhou, Yan
author_sort Guo, Huijuan
collection PubMed
description This paper proposes a novel interconnected observer to get good estimates of attitude and gyro bias from high-noise vector measurements. The observer is derived based on the theory of nonlinear and linear cascade systems, and its error dynamics have the properties of global exponential stability and robustness to bounded noise. These properties ensure the convergence and boundedness of the attitude and gyro bias estimation errors. To obtain higher estimation accuracy, an approach to calculate time-varying gains for the proposed auxiliary observer is designed under the premise of considering noise terms in the rate gyro and vector sensors. The simulation results show that when the vector sensors’ outputs contain high-level noise, the proposed observer with time-varying gains yields better performance in both the transient and steady-state phases.
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spelling pubmed-76973282020-11-29 A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements Guo, Huijuan Liu, Huiying Hu, Xiaoxiang Zhou, Yan Sensors (Basel) Article This paper proposes a novel interconnected observer to get good estimates of attitude and gyro bias from high-noise vector measurements. The observer is derived based on the theory of nonlinear and linear cascade systems, and its error dynamics have the properties of global exponential stability and robustness to bounded noise. These properties ensure the convergence and boundedness of the attitude and gyro bias estimation errors. To obtain higher estimation accuracy, an approach to calculate time-varying gains for the proposed auxiliary observer is designed under the premise of considering noise terms in the rate gyro and vector sensors. The simulation results show that when the vector sensors’ outputs contain high-level noise, the proposed observer with time-varying gains yields better performance in both the transient and steady-state phases. MDPI 2020-11-14 /pmc/articles/PMC7697328/ /pubmed/33202646 http://dx.doi.org/10.3390/s20226514 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Guo, Huijuan
Liu, Huiying
Hu, Xiaoxiang
Zhou, Yan
A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements
title A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements
title_full A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements
title_fullStr A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements
title_full_unstemmed A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements
title_short A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements
title_sort global interconnected observer for attitude and gyro bias estimation with vector measurements
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7697328/
https://www.ncbi.nlm.nih.gov/pubmed/33202646
http://dx.doi.org/10.3390/s20226514
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