ELM and LOS Based Path Tracking for Autonomous Underwater Vehicles

AUV is a typical nonlinear system which uncertainty of system model, and it is also affected by many external disturbances during the process of sailing, especially ocean currents and waves. Therefore, it is difficult to ensure path tracking control of AUV during navigation. A tracking control method based on the Extreme Learning Machine (ELM) and line of sight (LOS) was proposed to achieve robust path tracking. This method can add lateral velocity during sample training to reduce the impact of ocean currents and use the good real-thne nature of ELM to predict path points, then desired heading is calculated based on the principle of LOS and the classic PID is used as a controller for heading, depth and speed of AUV. Experimental results demonstrate that our tracking control system based on ELM and LOS enable AUV to move steadily along the planning path in a complex real-world environment.