LAUSR

This study proposes an integrated Fault Diagnosis (FDD) and Fault-Tolerant Control (FTC) framework aimed at enhancing the operational stability of Remotely Operated Vehicles (ROVs) by addressing thruster faults that compromise mission safety. The proposed methodology utilizes a data-driven FDD system, based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, to identify propeller breakage and entanglement faults from thruster current and Revolutions Per Minute (RPM) data. Based on the diagnostic results, an adaptive FTC strategy is activated, applying a ‘Thrust Compensation’ model for breakage faults and an ‘Exclusion and Reallocation’ approach for entanglement faults. The performance of the framework was validated through experiments in an engineering water tank, where results demonstrated a significant improvement in the ROV’s hovering stability and control accuracy under fault conditions. The system successfully restored thrust balance during breakage scenarios and maintained a stable attitude after excluding an entangled thruster. Consequently, the proposed adaptive FDD-FTC framework provides an effective solution for enhancing the operational reliability and safety of ROVs.