Among the key technologies of Autonomous Underwater Vehicle (AUV) leader–follower formations control, formation reconfiguration technology is one of the main technologies to ensure that multiple AUVs successfully complete their tasks in a complex operating environment. The biggest drawback of the leader–follower formations technology is the failure of the leader and the excessive communication pressure of the leader. Aiming at the problem of leader failure in multi- AUV leader–follower formations, the Hungarian algorithm is used to reconstruct the failed formation with a minimum cost, and the improvement of the Hungarian algorithm can solve the problem of a non-standard assignment. In order to solve the problem of an increased leader communication task after formation reconfiguration, the application of an event-triggered mechanism (ETM) can reduce unnecessary and useless communication, while the efficiency of the ETM can be improved through increasing the event-triggered conditions of the sampling error threshold. The simulation results of multi-AUV formation control show that the Hungarian algorithm proposed in this paper can deal with the leader failure in the multi-AUV leader–follower formation, and the ETM designed in this paper can reduce about 90% of the communication traffic of the formation which also proves the highly efficient performance of the improved ETM in the paper.

For the problem of hydroacoustic communication constraints in multi-AUV leader follower formation, this paper designs a formation control method combining CNN-LSTM prediction and backstepping sliding mode control. First, a feedback linearization method is used to transform the AUV nonlinear model into a second-order integral model; then, the influence of hydroacoustic communication constraints on the multi-AUV formation control problem is analyzed, and a sliding window-based formation prediction control strategy is designed; for the characteristics of AUV motion trajectory with certain temporal order, the CNN-LSTM prediction model is selected to predict the trajectory state of the leader follower and compensate the effect of communication delay on formation control, and combine the backstepping method and sliding mode control to design the formation controller. Finally, the simulation experimental results show that the proposed CNN-LSTM prediction and backstepping sliding mode control can improve the effect of hydroacoustic communication constraints on formation control.

This paper focuses on the finite-time formation-control problem of a multi-AUV formation under unknown perturbations with prescribed performance. First, the nonlinear AUV model is transformed into a second-order integral model using feedback linearization. Suitable prescribed performance functions are selected to constrain the control errors of AUVs within a preset range and convert AUV tracking errors into unconstrained tracking errors using an error-conversion function to facilitate controller design. Finite-time sliding-mode disturbance observers are designed for unknown disturbances in the ocean so that they can accurately estimate the unknown disturbances in finite time. Based on the unconstrained tracking error and the unknown disturbance observer, the fast terminal sliding-mode formation controller is designed so that the multi-AUV formation can converge in finite time. Finally, the simulation experimental results show that the finite-time formation-control method with prescribed performance proposed in this paper can better cancel the unknown disturbance in the ocean in finite time and improve the robustness of the multi-AUV formation control.