Adaptive neural trajectory tracking non-affine control for a hovercraft subject to multiple safety constraints

ABSTRACT

Considering the internal, external uncertainties and robustness decreases, this paper addresses an adaptive neural trajectory tracking non-affine control method for a hovercraft under multiple safety constraints. Firstly, hovercraft’s non-affine model has been built and aim to approximate non-affine formulations, a neural network (NN) is utilized. Secondly, to stabilize the position errors, virtual surge velocity control law is obtained via a log-type barrier Lyapunov function (LBLF). Thirdly, a new asymmetric integral barrier Lyapunov function (AIBLF) is presented to address asymmetric safety constraint problems of hovercraft. Aim to guarantee heading control, the yaw angular velocity is obtained consequently. The proposed adaptive method can guarantee the surge velocity and yaw angular velocity to the inside of asymmetric boundaries with the requirements of safe performance during motion. The total system states are ultimately uniformly bounded (UUB) via Lyapunov stability theories. Finally, obtained simulations results demonstrate the effectiveness of the proposed control scheme.

KEYWORDS:

• Hovercraft
• asymmetrical integral BLF
• trajectory tracking control
• state constraint

Acknowledgements

The authors would like to thank the editors and anonymous reviewers for their valuable comments and constructive suggestions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was funded by the National Natural Science Foundation of China, grant numbers 52071112 and 51309062; Fundamental Research Funds for the Central Universities, grant number 3072020CF0408 and Research on Maneuverability of High Speed Hovercraft, project number 2007DFR80320.

Notes on contributors

Qiusu Wang

Qiusu Wang was born in Jiangsu, China, in 1996. She received her BS degree from the College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, China, in 2018. She is currently pursuing her PhD degree in control science and engineering with Harbin Engineering University, Harbin. Her current research interests include ship motion and control and hovercraft safe navigation.

Mingyu Fu

Mingyu Fu was born in Jilin, China in 1964. She received her BS and MS degrees from Harbin Marine Engineering College and her PhD degree from Harbin Engineering University, where she is currently a professor and a PhD supervisor of control science and engineering with the College of Automation. Her current research interests include ship motion and control, multisensory fusion, intelligent system control, dynamic positioning systems for ships, hovercraft safe navigation and coordinated formation control for multiple ships.

Yuchao Wang

Yuchao Wang was born in China, in 1980. He received her BS and MS degrees from the Harbin Marine Engineering College and his PhD degree from Harbin Engineering University. His current research interests include ship motion and control, multisensory fusion, intelligent system control, dynamic positioning systems for ships and coordinated formation control for multiple ships.