Trajectory Tracking Control of AUV Formation Systems based on Adaptive Nonlinear Model Predictive Control

The objective of this work is to examine the difficulty of accomplishing multi-AUV trajectory tracking in underwater environments, which is essential for several underwater jobs like patrol, surveillance, and environment identification. The paper proposes a distributed nonlinear model predictive formation control based on adaptive prediction interval, which enables the achievement of AUV formation tracking and reduction in the computational burden associated with formation tasks. Firstly, a distributed auxiliary control law is proposed to ensure terminal convergence of the prediction interval of the AUV formation system. Second, by creating various constraint terms and adaptive prediction interval in the distributed nonlinear model predictive control (NMPC), the suggested technique tackles the problem of computationally cumbersome and input saturation. Then, by addressing a local MPC optimization problem that considers the state information of the AUV and its neighbors, the control input for every AUV is ascertained. Finally, the coordination and stability of the suggested predictive control system are shown by the presentation of numerical simulation results.