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Preview Control with Dynamic Constraints for Autonomous Vehicles

In this paper, a preview theory-based steering control approach considering vehicle dynamic constraints is presented. The constrained variables are predicted by an error states system and utilized to adjust the control law once the established dynamic constraints are violated. The simulated annealin...

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Detalles Bibliográficos
Autores principales: Li, Rui, Ouyang, Qi, Cui, Yue, Jin, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8347934/
https://www.ncbi.nlm.nih.gov/pubmed/34372392
http://dx.doi.org/10.3390/s21155155
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author Li, Rui
Ouyang, Qi
Cui, Yue
Jin, Yang
author_facet Li, Rui
Ouyang, Qi
Cui, Yue
Jin, Yang
author_sort Li, Rui
collection PubMed
description In this paper, a preview theory-based steering control approach considering vehicle dynamic constraints is presented. The constrained variables are predicted by an error states system and utilized to adjust the control law once the established dynamic constraints are violated. The simulated annealing optimization algorithm for preview length is conducted to improve the adaptability of the controller to varying velocities and road adhesion coefficients. The theoretical stability of a closed-loop system is guaranteed using Lyapunov theory, and further analysis of the system response in time domain and frequency domain is discussed. The results of simulations implemented on Carsim–Simulink demonstrate the favorable performance of the proposed control in tracking accuracy and system stability under extreme conditions.
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spelling pubmed-83479342021-08-08 Preview Control with Dynamic Constraints for Autonomous Vehicles Li, Rui Ouyang, Qi Cui, Yue Jin, Yang Sensors (Basel) Article In this paper, a preview theory-based steering control approach considering vehicle dynamic constraints is presented. The constrained variables are predicted by an error states system and utilized to adjust the control law once the established dynamic constraints are violated. The simulated annealing optimization algorithm for preview length is conducted to improve the adaptability of the controller to varying velocities and road adhesion coefficients. The theoretical stability of a closed-loop system is guaranteed using Lyapunov theory, and further analysis of the system response in time domain and frequency domain is discussed. The results of simulations implemented on Carsim–Simulink demonstrate the favorable performance of the proposed control in tracking accuracy and system stability under extreme conditions. MDPI 2021-07-29 /pmc/articles/PMC8347934/ /pubmed/34372392 http://dx.doi.org/10.3390/s21155155 Text en © 2021 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
Li, Rui
Ouyang, Qi
Cui, Yue
Jin, Yang
Preview Control with Dynamic Constraints for Autonomous Vehicles
title Preview Control with Dynamic Constraints for Autonomous Vehicles
title_full Preview Control with Dynamic Constraints for Autonomous Vehicles
title_fullStr Preview Control with Dynamic Constraints for Autonomous Vehicles
title_full_unstemmed Preview Control with Dynamic Constraints for Autonomous Vehicles
title_short Preview Control with Dynamic Constraints for Autonomous Vehicles
title_sort preview control with dynamic constraints for autonomous vehicles
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8347934/
https://www.ncbi.nlm.nih.gov/pubmed/34372392
http://dx.doi.org/10.3390/s21155155
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AT ouyangqi previewcontrolwithdynamicconstraintsforautonomousvehicles
AT cuiyue previewcontrolwithdynamicconstraintsforautonomousvehicles
AT jinyang previewcontrolwithdynamicconstraintsforautonomousvehicles