A Prognosis Technique Based on Improved GWO-NMPC to Improve the Trajectory Tracking Control System Reliability of Unmanned Underwater Vehicles

The dynamics model of the unmanned underwater vehicle (UUV) system is highly nonlinear, multi-degree-of-freedom, strongly coupled, and time-varying. Its motion control has been a complex problem due to unknown information about uncertainty working environment. To improve performance reliability UUV trajectory tracking control, method based on nonlinear predictive designed, an improved gray wolf optimization (IGWO) proposed for control. convergence factor IGWO designed as attenuation function, memory function added position update equation enhance effect Through simulation in ROS environment, influence rate error obtained. By comparing effects several groups reference trajectories, it shown that universally applicable effective UUV. Compared with traditional (GWO), SQP, other algorithms, demonstrated.