Adaptive Fuzzy Control of USV Based on Improved Finite-Time Command-Filtered Backstepping Method

This article introduces a path tracking control method for unmanned surface vehicle (USV), which uses finite-time adaptive fuzzy technology combined with command filter. Divide the path tracking control problem into the design of line of sight (LOS) guidance law and controller. Firstly, in response to disturbances in the marine environment, a side slip angle update rate and expected guidance angle are designed. Secondly, an adaptive fuzzy control strategy is proposed to approximate and compensate for model uncertainty and changes in state variables, in order to improve system robustness. Simultaneously utilizing an improved finite-time command filter and backstepping method to control the required guidance angle for yaw angle tracking. Finally, design an improved compensation mechanism to make the tracking control of the system more precise. The effectiveness of this method is verified through MATLAB simulation results.

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Institutions

Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3562579
Citations
3
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
1.60

Funders

Controls
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article

Adaptive Fuzzy Control of USV Based on Improved Finite-Time Command-Filtered Backstepping Method

Baofang Wang, Jiayu Liu
3 citations
IEEE Access
Power Systems and Renewable Energy
1.60
article

Adaptive Fuzzy Control of USV Based on Improved Finite-Time Command-Filtered Backstepping Method

Baofang Wang, Jiayu Liu
article en
3 citations

Abstract

This article introduces a path tracking control method for unmanned surface vehicle (USV), which uses finite-time adaptive fuzzy technology combined with command filter. Divide the path tracking control problem into the design of line of sight (LOS) guidance law and controller. Firstly, in response to disturbances in the marine environment, a side slip angle update rate and expected guidance angle are designed. Secondly, an adaptive fuzzy control strategy is proposed to approximate and compensate for model uncertainty and changes in state variables, in order to improve system robustness. Simultaneously utilizing an improved finite-time command filter and backstepping method to control the required guidance angle for yaw angle tracking. Finally, design an improved compensation mechanism to make the tracking control of the system more precise. The effectiveness of this method is verified through MATLAB simulation results.

IEEE AccessVol. 13
Qingdao University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 16%
Power Systems and Renewable Energy
1.60
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