Energy Consumption Optimization Strategy for Autonomous Underwater Vehicles Based on Model Prediction Control

Enhancing the endurance of autonomous underwater vehicles (AUVs) is an important foundation for AUVs to be able to perform various types of complex missions as well as return safely. In this paper, for the problem of insufficient energy during the AUV mission, an energy-saving model predictive controller is proposed to reduce the control energy of the AUV when it returns back and avoid the risk of loss of connection caused by energy exhaustion of the AUV. Firstly, the dynamics model of the AUV and the energy consumption model of the power system are established, and it is analyzed that the propellers are the main energy consumption source, due to the existence of the base system energy consumption, the energy consumption can be reduced by optimizing the surge speed. Secondly, leveraging conventional line-of-sight (LOS) guidance for reference tracking, the proposed controller tracks the desired heading and optimal surge velocity within the model prediction framework. Through simulation results, it is demonstrated that the proposed method effectively minimizes energy loss during the return phase.