Integral-Type Event-Triggered Model Predictive Hovering Control For Variable Buoyancy Autonomous Underwater Vehicle

This paper addresses the hover control challenge of an Autonomous Underwater Vehicle (AUV) equipped with a Variable Buoyancy System (VBS). Due to the discrete switching characteristics of VBS, the control input is restricted to three discrete action values. To overcome this limitation, we propose a Model Predictive Control (MPC) scheme based on an Integral-Type Event-Triggered Mechanism (IT-ETM). By incorporating the integral of the error between the predicted and actual state sequences, the proposed event-triggering condition effectively decreases the frequency of solving optimization problems, thereby conserving computational resources. Moreover, leveraging the ability of MPC to handle state and input constraints, the scheme achieves precise hover control despite the discrete nature of VBS control inputs. Finally, numerical simulations demonstrate the feasibility and robustness of the proposed method.