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![Quantitative results for the proposed scheme and the one in [15].](publication/370697730/figure/tbl1/AS:11431281157764135@1683901702159/Quantitative-results-for-the-proposed-scheme-and-the-one-in-15_Q320.jpg)
This paper focuses on the intervehicle security-based robust formation control of unmanned surface vehicles (USVs) to implement the formation switch mission. In the scheme, a novel adaptive potential ship (APS)-based guidance principle is developed to prevent intervehicle collisions, which is common and threatening when maneuvering a formation swit...
Contexts in source publication
Context 1
... the tracking errors were small enough compared with the scale of the formation route. Figure 7 describes the velocities of each USV. It shows that all the USVs reached the expected surge velocities in the formation-keeping period. ...
Context 2
... the tracking errors were small enough compared with the scale of the formation route. Figure 7 describes the velocities of each USV. It shows that all the USVs reached the expected surge velocities in the formation-keeping period. ...
Citations
... According to the research by Cui et al. [11], these external disturbances and model uncertainties that degrade the system performance negatively are referred to as compound disturbances. In response to these challenges, researchers have developed diverse schemes, such as disturbance observers [12], fuzzy logic theory [13], and neural networks [14]. Among these, the extended state observer (ESO) initially proposed by Han [15] is an attractive option to estimate compound disturbances, as it does not rely on an accurate model. ...
This paper focuses on the collision-free formation tracking of autonomous underwater vehicles (AUVs) with compound disturbances in complex ocean environments. We propose a novel finite-time extended state observer (FTESO)-based distributed dual closed-loop model predictive control scheme. Initially, a fast FTESO is designed to accurately estimate both model uncertainties and external disturbances for each subsystem. Subsequently, the outer-loop and inner-loop formation controllers are developed by integrating disturbance compensation with distributed model predictive control (DMPC) theory. With full consideration of the input and state constraints, we resolve the local information-based DMPC optimization problem to obtain the control inputs for each AUV, thereby preventing actuator saturation and collisions among AUVs. Moreover, to mitigate the increased computation caused by the control structure, the Laguerre orthogonal function is applied to alleviate the computational burden in time intervals. We also demonstrate the stability of the closed-loop system by applying the terminal state constraint. Finally, based on a connected directed topology, comparative simulations are performed under various control schemes to verify the robustness and superior performance of the proposed scheme.
