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Prescribed performance LOS guidance-based dynamic surface path following control of surface vessel with position and heading errors constraint

Published online by Cambridge University Press:  18 April 2023

Zhipeng Shen
Affiliation:
College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China
Ang Li
Affiliation:
College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China
Li Li
Affiliation:
College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China
Haomiao Yu*
Affiliation:
College of Marine Electrical Engineering, Dalian Maritime University, Dalian, People's Republic of China
*
*Corresponding author. Haomiao Yu; E-mail: yuhaomiao1983@163.com

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.

Type
Research Article
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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