Benoît Clement

Control Reallocation Using Deep Reinforcement Learning for Actuator Fault Recovery of an Autonomous Underwater Vehicle

Actuator faults in dynamic systems pose significant challenges, particularly for robotic systems operating in hostile environments such as Autonomous Underwater Vehicles (AUVs), risking loss of stability and performance degradation. Fault Tolerant Control (FTC) strategies, including Control Realloca