A Neural Dynamics Model Prediction-Based Adaptive Control System for AUV Formation Control

Objectives Provide a solution for the formation control issue that arises when AUVs are subjected to interference from obstacles and complex ocean currents. Methods To tackle the issue of AUV hysteresis resulting from an overly rapid predicted convergence speed during dynamic obstacle avoidance, a multi AUV formation adaptive control method (NDP-ABS) based on brain dynamics model prediction was created. In order to solve the local optimization problem of potential field methods, active and inhibitory sources were created. When paired with optimal control, dynamic obstacle avoidance, formation control, and predicted tracking were accomplished. Second, a nonlinear adaptive backstepping method is used to design the AUV expected tracking controller, which resolves the interference of shallow ocean current disturbances and nonlinear factors on the AUV expected tracking control. This is done in consideration of the unknown nonlinear factors and ocean current disturbances introduced in the control law of the NDP process. Finally, Lyapunov theory was used to demonstrate the system's stability. Results The anti-interference and obstacle avoidance performance of the NDP-ABS system was tested using six sets of comparative simulation tests, and the simulation results confirmed its efficacy. Conclusions The NDP-ABS formation scheme offers several benefits, including cheap obstacle avoidance costs, robust resistance to interference from ocean currents, high stability, and clear advantages in non-explicit formation control of multiple autonomous underwater vehicles.