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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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5500310?pdf=render |
| _version_ | 1818607461343428608 |
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| author | Mohanad M Hammad Ahmed K Elshenawy M I El Singaby |
| author_facet | Mohanad M Hammad Ahmed K Elshenawy M I El Singaby |
| author_sort | Mohanad M Hammad |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-16T14:27:07Z |
| format | Article |
| id | doaj.art-e6ddf4cde14e4fb6bea846ddb1804c77 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-16T14:27:07Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-e6ddf4cde14e4fb6bea846ddb1804c772022-12-21T22:28:20ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01127e017961110.1371/journal.pone.0179611Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID.Mohanad M HammadAhmed K ElshenawyM I El SingabyIn 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.http://europepmc.org/articles/PMC5500310?pdf=render |
| spellingShingle | Mohanad M Hammad Ahmed K Elshenawy M I El Singaby Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID. PLoS ONE |
| 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 |
| url | http://europepmc.org/articles/PMC5500310?pdf=render |
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