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Adaptive fixed-time path following cooperative control for autonomous surface vehicles based on path-dependent constraints
https://orcid.org/0000-0002-1577-571X
Abstract This paper introduces a fixed-time adaptive path-following cooperative control approach for autonomous surface vehicles (ASVs), aimed at improving navigation accuracy and safety in practical scenarios. The scheme ensures that ASVs accurately follow the reference path during navigation while satisfying position and heading angle constraints. To address the position constraint challenge, an adapted version of the universal barrier Lyapunov function is employed for path-dependent constraint function. Furthermore, a novel form of path-dependent constraint function is introduced, relying on path parameters instead of direct time variables. A new adaptive backstepping technique is also developed to tackle fixed-time convergence issues, mitigate the complexity surge in controller design, and account for the model’s uncertain dynamics. The study demonstrates that this control scheme enables the ASV’s position and heading errors to converge near the equilibrium point at a fixed time rate while consistently satisfying path-dependent constraints. The efficacy of the proposed scheme is further verified through simulation and experimental studies.
Adaptive fixed-time path following cooperative control for autonomous surface vehicles based on path-dependent constraints
https://orcid.org/0000-0002-1577-571X
Abstract This paper introduces a fixed-time adaptive path-following cooperative control approach for autonomous surface vehicles (ASVs), aimed at improving navigation accuracy and safety in practical scenarios. The scheme ensures that ASVs accurately follow the reference path during navigation while satisfying position and heading angle constraints. To address the position constraint challenge, an adapted version of the universal barrier Lyapunov function is employed for path-dependent constraint function. Furthermore, a novel form of path-dependent constraint function is introduced, relying on path parameters instead of direct time variables. A new adaptive backstepping technique is also developed to tackle fixed-time convergence issues, mitigate the complexity surge in controller design, and account for the model’s uncertain dynamics. The study demonstrates that this control scheme enables the ASV’s position and heading errors to converge near the equilibrium point at a fixed time rate while consistently satisfying path-dependent constraints. The efficacy of the proposed scheme is further verified through simulation and experimental studies.
Adaptive fixed-time path following cooperative control for autonomous surface vehicles based on path-dependent constraints
https://orcid.org/0000-0002-1577-571X
Abstract This paper introduces a fixed-time adaptive path-following cooperative control approach for autonomous surface vehicles (ASVs), aimed at improving navigation accuracy and safety in practical scenarios. The scheme ensures that ASVs accurately follow the reference path during navigation while satisfying position and heading angle constraints. To address the position constraint challenge, an adapted version of the universal barrier Lyapunov function is employed for path-dependent constraint function. Furthermore, a novel form of path-dependent constraint function is introduced, relying on path parameters instead of direct time variables. A new adaptive backstepping technique is also developed to tackle fixed-time convergence issues, mitigate the complexity surge in controller design, and account for the model’s uncertain dynamics. The study demonstrates that this control scheme enables the ASV’s position and heading errors to converge near the equilibrium point at a fixed time rate while consistently satisfying path-dependent constraints. The efficacy of the proposed scheme is further verified through simulation and experimental studies.
Adaptive fixed-time path following cooperative control for autonomous surface vehicles based on path-dependent constraints
Guo, Qiang (author) / Zhang, Xianku (author) / Ma, Daocheng (author)
Applied Ocean Research ; 142
2023-11-27
Article (Journal)
Electronic Resource
English
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