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Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

In this paper, an output-feedback fuzzy adaptive dynamic surface controller (FADSC) based on fuzzy adaptive extended state observer (FAESO) is proposed for autonomous underwater vehicle (AUV) systems in the presence of external disturbances, parameter uncertainties, measurement noises and actuator f...

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Detalles Bibliográficos
Autores principales: Kang, Song, Rong, Yongfeng, Chou, Wusheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763566/
https://www.ncbi.nlm.nih.gov/pubmed/33321909
http://dx.doi.org/10.3390/s20247084
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author Kang, Song
Rong, Yongfeng
Chou, Wusheng
author_facet Kang, Song
Rong, Yongfeng
Chou, Wusheng
author_sort Kang, Song
collection PubMed
description In this paper, an output-feedback fuzzy adaptive dynamic surface controller (FADSC) based on fuzzy adaptive extended state observer (FAESO) is proposed for autonomous underwater vehicle (AUV) systems in the presence of external disturbances, parameter uncertainties, measurement noises and actuator faults. The fuzzy logic system is incorporated into both the observers and controllers to improve the adaptability of the entire system. The dynamics of the AUV system is established first, considering the external disturbances and parameter uncertainties. Based on the dynamic models, the ESO, combined with a fuzzy logic system tuning the observer bandwidth, is developed to not only adaptively estimate both system states and the lumped disturbances for the controller, but also reduce the impact of measurement noises. Then, the DSC, together with fuzzy logic system tuning the time constant of the low-pass filter, is designed using estimations from the FAESO for the AUV system. The asymptotic stability of the entire system is analyzed through Lyapunov’s direct method in the time domain. Comparative simulations are implemented to verify the effectiveness and advantages of the proposed method compared with other observers and controllers considering external disturbances, parameter uncertainties and measurement noises and even the actuator faults that are not considered in the design process. The results show that the proposed method outperforms others in terms of tracking accuracy, robustness and energy consumption.
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spelling pubmed-77635662020-12-27 Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer Kang, Song Rong, Yongfeng Chou, Wusheng Sensors (Basel) Article In this paper, an output-feedback fuzzy adaptive dynamic surface controller (FADSC) based on fuzzy adaptive extended state observer (FAESO) is proposed for autonomous underwater vehicle (AUV) systems in the presence of external disturbances, parameter uncertainties, measurement noises and actuator faults. The fuzzy logic system is incorporated into both the observers and controllers to improve the adaptability of the entire system. The dynamics of the AUV system is established first, considering the external disturbances and parameter uncertainties. Based on the dynamic models, the ESO, combined with a fuzzy logic system tuning the observer bandwidth, is developed to not only adaptively estimate both system states and the lumped disturbances for the controller, but also reduce the impact of measurement noises. Then, the DSC, together with fuzzy logic system tuning the time constant of the low-pass filter, is designed using estimations from the FAESO for the AUV system. The asymptotic stability of the entire system is analyzed through Lyapunov’s direct method in the time domain. Comparative simulations are implemented to verify the effectiveness and advantages of the proposed method compared with other observers and controllers considering external disturbances, parameter uncertainties and measurement noises and even the actuator faults that are not considered in the design process. The results show that the proposed method outperforms others in terms of tracking accuracy, robustness and energy consumption. MDPI 2020-12-10 /pmc/articles/PMC7763566/ /pubmed/33321909 http://dx.doi.org/10.3390/s20247084 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
Kang, Song
Rong, Yongfeng
Chou, Wusheng
Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer
title Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer
title_full Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer
title_fullStr Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer
title_full_unstemmed Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer
title_short Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer
title_sort antidisturbance control for auv trajectory tracking based on fuzzy adaptive extended state observer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763566/
https://www.ncbi.nlm.nih.gov/pubmed/33321909
http://dx.doi.org/10.3390/s20247084
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