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A finite-time path following scheme of unmanned surface vessels with an optimization strategy
The path-following problem of unmanned surface vessels (USVs) is solved in this paper, considering unknown interference, energy-saving strategy, input constraints, and input rate of change constraints. Firstly, the USV model considering lumped interference is given, while an interference observer ba...
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Published in: | ISA transactions 2024-03, Vol.146, p.61-74 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The path-following problem of unmanned surface vessels (USVs) is solved in this paper, considering unknown interference, energy-saving strategy, input constraints, and input rate of change constraints. Firstly, the USV model considering lumped interference is given, while an interference observer based on finite-time theory is used for interference estimation where the convergence time is specified. Then, to accelerate the USV convergence to a given path, a novel improved adaptive finite-time line-of-sight (IAFTLOS) scheme is developed. The proposed IAFTLOS scheme makes the cross-path error with finite-time convergence. At the same time, an adaptive time-varying looking distance law is designed to improve the convergence performance further. Next, nonlinear model predictive control is introduced to deal with rates of change and input constraints. In addition, an energy-saving strategy is incorporated into the design of the controller. Finally, stable control of the whole cascade system is achieved, and comparative simulation cases verify the feasibility and robustness of the entire system.
•A finite-time interference observer with a deterministic convergence time is designed to estimate system interference.•Design of an improved finite-time guidance scheme with a faster convergence speed.•A novel adaptive looking distance rule is used to improve the convergence speed further.•Nonlinear model predictive control is used to provide an energy-saving strategy and deal with constraints. |
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ISSN: | 0019-0578 1879-2022 |
DOI: | 10.1016/j.isatra.2024.01.016 |