SOURCE-LINKED INTELLIGENCE

Fault Diagnosis for Underwater Vehicles using Moving Horizon Estimation and Gaussian Processes

arXiv · AI, language, vision and robotics · article · Sep 13, 2026 · UTC

This work proposes a model-based fault detection and diagnosis framework for underwater vehicles subject to actuator faults that explicitly accounts for the presence of unmodeled dynamics. To this end, a Moving Horizon Estimator (MHE) is developed to estimate the lumped disturbance, capturing both unmodeled and fault effects. Gaussian Processes (GPs) are employed to approximate the unmodeled dynamics, providing predictions of the corresponding mean and uncertainty across diverse operating conditions. During online operation, the residual between the MHE lumped disturbance estimate and the GP p

Read original source ↗ Open in workspace

recordType

paper

region

Global