Robust Model-Based Fault Diagnosis for Unmanned Underwater Vehicles Using Sliding Mode-Observers

摘要

The early detection of the malfunctions and faults as well as their compensation is crucial both for maintenance and for mission reliability of unmanned underwater vehicles (UUVs). Among the different fault detection methods using analytical redundancy, the first distinction rises between model- free and model-based approaches. Model-free methods are well-suited for large- scale systems, where the development of a model is too expensive. The lumped parameter model of an underwater vehicle can be easily described by a small set of well-known equations with highly uncertain parameters. This uncertainty suggests the introduction of robustness requirements in the model-based residual generation for UUVs. Robustness can be addressed in many different ways. According to the same view, the so-called unknown input observer (UIO) has been proposed. These approaches share the common idea of decoupling residuals and noises by eliminating (or at least reducing in some optimal sense) the influence of the disturbances on the residuals.