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Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data

In this paper, a novel model predictive control (MPC) method based on the population normal probability division genetic algorithm and ant colony optimization (GA-ACO) method is proposed to optimally solve the problem of standard MPC with constraints that generally cannot yield global optimal soluti...

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Detalles Bibliográficos
Autores principales: Bao, Han, Zhu, Haitao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185449/
https://www.ncbi.nlm.nih.gov/pubmed/35684855
http://dx.doi.org/10.3390/s22114234
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author Bao, Han
Zhu, Haitao
author_facet Bao, Han
Zhu, Haitao
author_sort Bao, Han
collection PubMed
description In this paper, a novel model predictive control (MPC) method based on the population normal probability division genetic algorithm and ant colony optimization (GA-ACO) method is proposed to optimally solve the problem of standard MPC with constraints that generally cannot yield global optimal solutions when using quadratic programming (QP). Combined with dynamic sliding mode control (SMC), this model is applied to the dynamic trajectory tracking control of autonomous underwater vehicles (AUVs). First, the computational fluid dynamics (CFD) simulation platform ANSYS Fluent is used to solve for the main hydrodynamic coefficients required to establish the AUV dynamic model. Then, the novel model predictive controller is used to obtain the desired velocity command of the AUV. To reduce the influence of external interference and realize accurate velocity tracking, dynamic SMC is used to obtain the control input command. In addition, stability analysis based on the Lyapunov method proves the asymptotic stability of the controller. Finally, the trajectory tracking performance of the AUV in an underwater, three-dimensional environment is verified by using the MATLAB/Simulink simulation platform. The results verify the effectiveness and robustness of the proposed control method.
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spelling pubmed-91854492022-06-11 Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data Bao, Han Zhu, Haitao Sensors (Basel) Article In this paper, a novel model predictive control (MPC) method based on the population normal probability division genetic algorithm and ant colony optimization (GA-ACO) method is proposed to optimally solve the problem of standard MPC with constraints that generally cannot yield global optimal solutions when using quadratic programming (QP). Combined with dynamic sliding mode control (SMC), this model is applied to the dynamic trajectory tracking control of autonomous underwater vehicles (AUVs). First, the computational fluid dynamics (CFD) simulation platform ANSYS Fluent is used to solve for the main hydrodynamic coefficients required to establish the AUV dynamic model. Then, the novel model predictive controller is used to obtain the desired velocity command of the AUV. To reduce the influence of external interference and realize accurate velocity tracking, dynamic SMC is used to obtain the control input command. In addition, stability analysis based on the Lyapunov method proves the asymptotic stability of the controller. Finally, the trajectory tracking performance of the AUV in an underwater, three-dimensional environment is verified by using the MATLAB/Simulink simulation platform. The results verify the effectiveness and robustness of the proposed control method. MDPI 2022-06-01 /pmc/articles/PMC9185449/ /pubmed/35684855 http://dx.doi.org/10.3390/s22114234 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bao, Han
Zhu, Haitao
Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data
title Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data
title_full Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data
title_fullStr Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data
title_full_unstemmed Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data
title_short Modeling and Trajectory Tracking Model Predictive Control Novel Method of AUV Based on CFD Data
title_sort modeling and trajectory tracking model predictive control novel method of auv based on cfd data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185449/
https://www.ncbi.nlm.nih.gov/pubmed/35684855
http://dx.doi.org/10.3390/s22114234
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