The control problem of avoidance-path-following is a critical consideration in the research of unmanned surface vehicle (USV) navigation control, and it holds great significance for the navigation safety of USVs. A guidance and control scheme based on finite-distance convergence is proposed in this paper. First, the requirements for the USV to avoid obstacles from the perspective of path-following lateral error are analyzed. Then, a new performance function with finite-distance convergence is proposed to constrain the lateral error. Based on this, a heading guidance law and a backstepping controller are designed to ensure that the lateral error converges to a steady-state value within the prescribed navigation distance and that the stability is maintained, satisfying the requirements of obstacle avoidance for the USV. In addition, an adaptive velocity command is designed to adjust the velocity with the lateral error, which, to a certain extent, avoids the saturation of the heading actuator caused by the large lateral error. Finally, it is proven through theory and simulation that the control algorithm can guide the USV to achieve avoidance-path-following within a limited distance and to avoid obstacles effectively.

This article investigates a prescribed-time trajectory tracking control strategy for USVs considering marine environmental interferences and unmodeled dynamics. Firstly, a fixed-time extended state observer is introduced to quickly and accurately observe the compound perturbations including ocean disturbances and unmodeled dynamics. Subsequently, a prescribed-time prescribed performance function is utilized to obtain guaranteed transient performance within a predefined time. Finally, combining the fixed-time extended state observer, dynamic surface control technique, and prescribed-time prescribed performance control, a prescribed-time prescribed performance control strategy is developed to guarantee that the tracking errors converge to a predefined performance constraint boundary within a prescribed time. The effectiveness and superiority of the presented control strategy is verified by the simulation results.

This study proposes a fixed-time precision tracking control scheme for unmanned surface vessels with complex disturbances and unknown system dynamics. The control scheme is based on a nonsingular fast terminal sliding mode and includes an adaptive fixed-time integral sliding mode lumped disturbance observer to precisely observe and compensate for lumped unknowns. To ensure system performance under both transient and steady-state conditions, a prescribed performance function was utilized to enable the trajectory tracking error to converge to a predetermined range. The proposed control scheme, called prescribed performance fixed-time precision tracking (PPFTPT), was designed to achieve precision tracking of a predetermined trajectory within a fixed time. The stability of the closed-loop system was analyzed using the Lyapunov stability theory. Simulation results using the Cybership II model confirmed the feasibility and superiority of the proposed PPFTPT scheme.

This paper investigates the challenging problem of fixed-time formation trajectory tracking control for multiple unmanned surface vessels (USVs) affected by uncertain model dynamics, time-varying external ocean disturbances, as well as input saturation. Firstly, an adaptive super-twisting lumped disturbance observer (ASTLDO) is created by integrating high-order sliding mode with observer technology, which can accurately observe and compensate for the complex disturbance of the system within a finite time. Secondly, following the disturbance observer, backstepping technique, fixed-time control, and virtual leader–follower algorithm, the fixed-time formation tracking strategy is implemented. The proposed formation tracking control scheme enables the multiple surface vessels system to converge and maintain a stable desired formation in a fixed time, and the convergence time is independent of the initial states of the system. Furthermore, an adaptive auxiliary system is introduced to mitigate input saturation. In the end, the effectiveness and anti-interference ability of the suggested approach are confirmed by the formation simulation results of three USVs.

Formation obstacle avoidance is a critical aspect of cooperation among unmanned surface vehicles (USVs). In practical scenarios involving multiple USVs, managing obstacle avoidance during formation assembly and navigation is essential to ensure the success of cooperative tasks. This study devised a formation cooperative obstacle-avoidance scheme utilizing dynamical systems (DS). The traditional interfered fluid dynamical system (IFDS) applied in two-dimensional planes was enhanced to address local minima issues. Furthermore, robust virtual structure patterns were implemented to effectively decouple velocity vectors. Streamlines were optimized by adjusting velocity amplitudes within specific distance intervals, facilitating precise formation assembly amidst multiple obstacles. Additionally, a novel inter-vehicle disturbance method, distinct from the IFDS, was developed to enhance inter-vehicle collision avoidance. The effectiveness of the proposed method in enabling USV formations to adeptly navigate obstacles while maintaining formation integrity and collision-avoidance capabilities was analyzed theoretically and confirmed through simulation.

Formation obstacle avoidance is an essential attribute of the cooperative task in unmanned surface vehicle (USV) formation. In real-world scenarios involving multiple USVs, both formation obstacle avoidance and formation recovery after obstacle avoidance play a critical role in ensuring the success of collaborative missions. In this study, an Interfered Fluid Dynamic System (IFDS) algorithm was used for obstacle avoidance due to its excellent robustness, high computational efficiency and path smoothness. The algorithm can provide good local path planning for USVs. However, the use of the IFDS on USVs still has the defect of local extreme values, which has been effectively modified to obtain an enhanced IFDS (EIFDS). In formation, based on the leader–follower method, the virtual leader was used to determine the desired position of USVs in formation, and the streamlines generated by the EIFDS guided the USVs. In order to make the formation converge to the desired formation better, the vector and scalar of the EIFDS algorithm were uncoupled, and different designs were made to achieve convergence to the desired formation. The interfered residue of the IFDS is not suitable for addressing collision avoidance between USVs in practice. Therefore, the vector field method was employed to tackle the issue, with some enhancements made to optimize its performance. Subsequently, a weighted separation method was applied to combine the vector field and EIFDS, resulting in a composite field solution. Finally, the formation obstacle avoidance strategy based on composite fields was formed. The feasibility of this scheme was verified by simulation, and compared with the single IFDS formation method, the pairwise spacing of USVs behind obstacles could be increased, and the reliability of formation obstacle avoidance was increased.