Distributed Robust Learning Control for Multiple Unmanned Surface Vessels With Fixed-Time Prescribed Performance

This article investigates the distributed formation control problem for multiple unmanned surface vessels (USVs) with model uncertainties, exogenous disturbance, and input saturation. First, a distributed finite-time sliding mode observer is developed to obtain the desired trajectory of each USV. Th...

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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2024-02, Vol.54 (2), p.1-13
Main Authors: Duan, Haibin, Yuan, Yang, Zeng, Zhigang
Format: Article
Language:English
Subjects:
Artificial neural networks
Composite learning control
Continuity (mathematics)
Control methods
Convergence
distributed finite-time sliding mode observer
Disturbance observers
fixed-time prescribed performance function
Learning
multiple USV formation
Reference signals
Robust control
Robustness
Sea surface
Solid modeling
Trajectory
Uncertainty
Vessels
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Summary:This article investigates the distributed formation control problem for multiple unmanned surface vessels (USVs) with model uncertainties, exogenous disturbance, and input saturation. First, a distributed finite-time sliding mode observer is developed to obtain the desired trajectory of each USV. Then, a second-order differentiable continuous fixed-time prescribed performance function is applied to reconstruct the error model based on the reference signal. In addition, the unknown part and disturbance are simultaneously handled by the composite learning control method as well as input saturation, where the NN, disturbance observer, auxiliary system, and nonsingular fast terminal sliding mode technique are integrated. Moreover, it is proved that the formation error converges to a small neighbor of the origin in a finite time. Finally, the computational simulation examples are conducted to validate the feasibility and effectiveness of the proposed method.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2023.3321119