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Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID

In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results...

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Autores principales: Hammad, Mohanad M., Elshenawy, Ahmed K., El Singaby, M.I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500310/
https://www.ncbi.nlm.nih.gov/pubmed/28683071
http://dx.doi.org/10.1371/journal.pone.0179611
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author Hammad, Mohanad M.
Elshenawy, Ahmed K.
El Singaby, M.I.
author_facet Hammad, Mohanad M.
Elshenawy, Ahmed K.
El Singaby, M.I.
author_sort Hammad, Mohanad M.
collection PubMed
description In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results from the hydrodynamics and the coupled AUV dynamics makes the design of a stable controller a very difficult task. In this study, the control scheme in a simulation environment is validated using dynamic and kinematic equations for the AUV model and hydrodynamic damping equations. An AUV configuration with eight thrusters and an inverse kinematic model from a previous work is utilized in the simulation. In the proposed controller, Mamdani fuzzy rules are used to tune the parameters of the PID. Nonlinear fuzzy Gaussian membership functions are selected to give better performance and response in the non-linear system. A control architecture with two feedback loops is designed such that the inner loop is for velocity control and outer loop is for position control. Several test scenarios are executed to validate the controller performance including different complex trajectories with and without injection of ocean current disturbances. A comparison between the proposed FPID controller and the conventional PID controller is studied and shows that the FPID controller has a faster response to the reference signal and more stable behavior in a disturbed non-linear environment.
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spelling pubmed-55003102017-07-11 Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID Hammad, Mohanad M. Elshenawy, Ahmed K. El Singaby, M.I. PLoS One Research Article In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results from the hydrodynamics and the coupled AUV dynamics makes the design of a stable controller a very difficult task. In this study, the control scheme in a simulation environment is validated using dynamic and kinematic equations for the AUV model and hydrodynamic damping equations. An AUV configuration with eight thrusters and an inverse kinematic model from a previous work is utilized in the simulation. In the proposed controller, Mamdani fuzzy rules are used to tune the parameters of the PID. Nonlinear fuzzy Gaussian membership functions are selected to give better performance and response in the non-linear system. A control architecture with two feedback loops is designed such that the inner loop is for velocity control and outer loop is for position control. Several test scenarios are executed to validate the controller performance including different complex trajectories with and without injection of ocean current disturbances. A comparison between the proposed FPID controller and the conventional PID controller is studied and shows that the FPID controller has a faster response to the reference signal and more stable behavior in a disturbed non-linear environment. Public Library of Science 2017-07-06 /pmc/articles/PMC5500310/ /pubmed/28683071 http://dx.doi.org/10.1371/journal.pone.0179611 Text en © 2017 Hammad et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hammad, Mohanad M.
Elshenawy, Ahmed K.
El Singaby, M.I.
Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID
title Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID
title_full Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID
title_fullStr Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID
title_full_unstemmed Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID
title_short Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID
title_sort trajectory following and stabilization control of fully actuated auv using inverse kinematics and self-tuning fuzzy pid
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500310/
https://www.ncbi.nlm.nih.gov/pubmed/28683071
http://dx.doi.org/10.1371/journal.pone.0179611
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