Fault-Tolerant Control of Remotely Operated Vehicle Thrusters Based on the Dung Beetle Optimizer

A biological population-based algorithm, the dung beetle optimizer, is used for thrust redistribution in the event of thruster failure in remotely operated vehicle (ROV). Firstly, a kinematic controller based on model predictive control is designed to process ROV position and attitude errors to achieve target position and speed. Secondly, sliding mode control is used for dynamic control to design the appropriate thrust so that the actual speed tracks the desired velocity. When the thruster fails, the dung beetle optimizer is used to find the optimal scheme of thruster thrust distribution, so that the trajectory tracking process can be consistent before and after the failure. The results of simulation experiments show that the proposed fault-tolerant control based on the dung beetle optimizer can effectively handle the trajectory tracking problem under thruster failure.