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Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles
Several control strategies have been proposed for the trajectory tracking problem of Autonomous Underwater Vehicles (AUV). Most of them are model-based, hence, detailed knowledge of the parameters of the robot is needed. Few works consider a finite-time convergence in their controllers, which offers...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780515/ https://www.ncbi.nlm.nih.gov/pubmed/35062449 http://dx.doi.org/10.3390/s22020488 |
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author | González-García, Josué Gómez-Espinosa, Alfonso García-Valdovinos, Luis Govinda Salgado-Jiménez, Tomás Cuan-Urquizo, Enrique Escobedo Cabello, Jesús Arturo |
author_facet | González-García, Josué Gómez-Espinosa, Alfonso García-Valdovinos, Luis Govinda Salgado-Jiménez, Tomás Cuan-Urquizo, Enrique Escobedo Cabello, Jesús Arturo |
author_sort | González-García, Josué |
collection | PubMed |
description | Several control strategies have been proposed for the trajectory tracking problem of Autonomous Underwater Vehicles (AUV). Most of them are model-based, hence, detailed knowledge of the parameters of the robot is needed. Few works consider a finite-time convergence in their controllers, which offers strong robustness and fast convergence compared with asymptotic or exponential solutions. Those finite-time controllers do not permit the users to predefine the convergence time, which can be useful for a more efficient use of the robot’s energy. This paper presents the experimental validation of a model-free high-order Sliding Mode Controller (SMC) with finite-time convergence in a predefined time. The convergence time is introduced by the simple change of a time-base parameter. The aim is to validate the controller so it can be implemented for cooperative missions where the communication is limited or null. Results showed that the proposed controller can drive the robot to the desired depth and heading trajectories in the predefined time for all the cases, reducing the error by up to 75% and 41% when compared with a PID and the same SMC with asymptotic convergence. The energy consumption was reduced 35% and 50% when compared with those same controllers. |
format | Online Article Text |
id | pubmed-8780515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87805152022-01-22 Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles González-García, Josué Gómez-Espinosa, Alfonso García-Valdovinos, Luis Govinda Salgado-Jiménez, Tomás Cuan-Urquizo, Enrique Escobedo Cabello, Jesús Arturo Sensors (Basel) Article Several control strategies have been proposed for the trajectory tracking problem of Autonomous Underwater Vehicles (AUV). Most of them are model-based, hence, detailed knowledge of the parameters of the robot is needed. Few works consider a finite-time convergence in their controllers, which offers strong robustness and fast convergence compared with asymptotic or exponential solutions. Those finite-time controllers do not permit the users to predefine the convergence time, which can be useful for a more efficient use of the robot’s energy. This paper presents the experimental validation of a model-free high-order Sliding Mode Controller (SMC) with finite-time convergence in a predefined time. The convergence time is introduced by the simple change of a time-base parameter. The aim is to validate the controller so it can be implemented for cooperative missions where the communication is limited or null. Results showed that the proposed controller can drive the robot to the desired depth and heading trajectories in the predefined time for all the cases, reducing the error by up to 75% and 41% when compared with a PID and the same SMC with asymptotic convergence. The energy consumption was reduced 35% and 50% when compared with those same controllers. MDPI 2022-01-09 /pmc/articles/PMC8780515/ /pubmed/35062449 http://dx.doi.org/10.3390/s22020488 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 González-García, Josué Gómez-Espinosa, Alfonso García-Valdovinos, Luis Govinda Salgado-Jiménez, Tomás Cuan-Urquizo, Enrique Escobedo Cabello, Jesús Arturo Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles |
title | Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles |
title_full | Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles |
title_fullStr | Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles |
title_full_unstemmed | Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles |
title_short | Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles |
title_sort | experimental validation of a model-free high-order sliding mode controller with finite-time convergence for trajectory tracking of autonomous underwater vehicles |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780515/ https://www.ncbi.nlm.nih.gov/pubmed/35062449 http://dx.doi.org/10.3390/s22020488 |
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