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ORIGINAL RESEARCH article
Front. Robot. AI
Sec. Robotic Control Systems
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1576171
This article is part of the Research Topic Learning and Adaptive Control Systems on Robotics View all 3 articles
Fuzzy Adaptive Fault-Tolerant Control for an Unmanned Surface Vehicle with Prescribed Tracking Performance
Provisionally accepted- 1 Nanjing University of Science and Technology, Nanjing, Jiangsu Province, China
- 2 704 Research Institute, Shanghai, China
Unmanned surface vehicles (USVs), as a type of marine robotic systems, are widely used in various applications such as maritime surveillance, environmental monitoring, and cargo transportation. This article addresses the trajectory tracking control issue for an USV subject to model uncertainties and actuator faults. A logarithm barrier Lyapunov functions based predefined tracking control scheme is proposed to regulate the position error of the USV into predefined performance region. Then, to ensure the predefined transient and steady state tracking performance of the USV in the presence of actuator faults, we propose an adaptive fuzzy fault-tolerant controller to address the actuator faults. Additionally, to deal with the uncertainties arising from the USV system model, fuzzy logic systems are utilized to estimate the unknown hydrodynamic parameters. Based on the Lyapunov stability criterion, it can be demonstrated that all the closed-loop signals are bounded. Finally, the validity of the developed control scheme is demonstrated from simulation results.
Keywords: Unmanned Surface Vehicles (USVs), Actuator faults, Trajectory tracking, Fault-tolerant control, Fuzzy adaptive control
Received: 13 Feb 2025; Accepted: 25 Mar 2025.
Copyright: © 2025 Bao, Gao and Peng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ji Gao, 704 Research Institute, Shanghai, China
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