Prescribed performance LOS guidance-based dynamic surface path following control of surface vessel with position and heading errors constraint
Concentrating on a surface vessel with input saturation, model uncertainties and unknown disturbances, a path following the adaptive backstepping control method based on prescribed performance line-of-sight (PPLOS) guidance is proposed. First, a prescribed performance asymmetric modified barrier Lya...
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Published in | Journal of navigation Vol. 76; no. 2-3; pp. 255 - 285 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Cambridge, UK
Cambridge University Press
01.03.2023
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Subjects | |
Online Access | Get full text |
ISSN | 0373-4633 1469-7785 |
DOI | 10.1017/S0373463323000061 |
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Abstract | Concentrating on a surface vessel with input saturation, model uncertainties and unknown disturbances, a path following the adaptive backstepping control method based on prescribed performance line-of-sight (PPLOS) guidance is proposed. First, a prescribed performance asymmetric modified barrier Lyapunov function (PPAMBLF) is used to design the PPLOS and the heading controller, which make the path following position and heading errors meet the prescribed performance requirements. Furthermore, the backstepping and dynamic surface technique (DSC) are used to design the path following controller and the adaptive assistant systems are constructed to compensate the influence of input saturation. In addition, neural networks are introduced to approximate model uncertainties, and the adaptive laws are designed to estimate the bounds of the neural network approximation errors and unknown disturbances. According to the Lyapunov stability theory, all signals are semi-globally uniformly ultimately bounded. Finally, a 76$\,{\cdot }\,$2 m supply surface vessel is used for simulation experiments. The experimental results show that although the control inputs are limited, the control system can still converge quickly, and both position and heading errors can be limited to the prescribed performance requirements. |
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AbstractList | Concentrating on a surface vessel with input saturation, model uncertainties and unknown disturbances, a path following the adaptive backstepping control method based on prescribed performance line-of-sight (PPLOS) guidance is proposed. First, a prescribed performance asymmetric modified barrier Lyapunov function (PPAMBLF) is used to design the PPLOS and the heading controller, which make the path following position and heading errors meet the prescribed performance requirements. Furthermore, the backstepping and dynamic surface technique (DSC) are used to design the path following controller and the adaptive assistant systems are constructed to compensate the influence of input saturation. In addition, neural networks are introduced to approximate model uncertainties, and the adaptive laws are designed to estimate the bounds of the neural network approximation errors and unknown disturbances. According to the Lyapunov stability theory, all signals are semi-globally uniformly ultimately bounded. Finally, a 76
$\,{\cdot }\,$
2 m supply surface vessel is used for simulation experiments. The experimental results show that although the control inputs are limited, the control system can still converge quickly, and both position and heading errors can be limited to the prescribed performance requirements. Concentrating on a surface vessel with input saturation, model uncertainties and unknown disturbances, a path following the adaptive backstepping control method based on prescribed performance line-of-sight (PPLOS) guidance is proposed. First, a prescribed performance asymmetric modified barrier Lyapunov function (PPAMBLF) is used to design the PPLOS and the heading controller, which make the path following position and heading errors meet the prescribed performance requirements. Furthermore, the backstepping and dynamic surface technique (DSC) are used to design the path following controller and the adaptive assistant systems are constructed to compensate the influence of input saturation. In addition, neural networks are introduced to approximate model uncertainties, and the adaptive laws are designed to estimate the bounds of the neural network approximation errors and unknown disturbances. According to the Lyapunov stability theory, all signals are semi-globally uniformly ultimately bounded. Finally, a 76$\,{\cdot }\,$2 m supply surface vessel is used for simulation experiments. The experimental results show that although the control inputs are limited, the control system can still converge quickly, and both position and heading errors can be limited to the prescribed performance requirements. |
Author | Yu, Haomiao Li, Li Shen, Zhipeng Li, Ang |
Author_xml | – sequence: 1 givenname: Zhipeng surname: Shen fullname: Shen, Zhipeng organization: College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China – sequence: 2 givenname: Ang surname: Li fullname: Li, Ang organization: College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China – sequence: 3 givenname: Li surname: Li fullname: Li, Li organization: College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China – sequence: 4 givenname: Haomiao orcidid: 0000-0001-6247-8614 surname: Yu fullname: Yu, Haomiao email: yuhaomiao1983@163.com organization: College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China |
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Snippet | Concentrating on a surface vessel with input saturation, model uncertainties and unknown disturbances, a path following the adaptive backstepping control... |
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SubjectTerms | Adaptive control Adaptive systems Approximation Control methods Control systems Control systems design Controllers Design Disturbances Engineering Errors Kinematics Liapunov functions Line of sight Neural networks Offshore Saturation Trajectory planning Uncertainty Velocity Vessels |
Title | Prescribed performance LOS guidance-based dynamic surface path following control of surface vessel with position and heading errors constraint |
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