Design of AUV Depth Control System based on PSO Algorithm Optimization

This research focuses on the depth control challenge of autonomous underwater vehicles (AUVs). A comprehensive dynamic model was developed utilizing MATLAB's computational capabilities. The control architecture employs a dual-layer PID framework with integrated feedback mechanisms. To optimize controller performance, an inertia weight particle swarm optimization (PSO) approach was implemented for parameter calibration. Simulation experiments are conducted in the MATLAB 2021b environment. The experimental results show that the control system can effectively track the desired depth, achieving depth-keeping navigation for the underwater vehicle.