Abstract
This chapter discusses fault detection and identification (FDI) in a buck DC/DC converter. A robust FDI methodology is proposed for contexts with bounded errors, taking into account the uncertainties in the parameters of a basic converter model. We begin by presenting one method of varying the parameters of a basic DC/DC converter over an interval (linear parameter varying [LPV]). In extreme environments, the components of the systems can change over time, and so our proposed LPV model must account for these changes. This chapter presents an interval predictor for detecting and identifying multiple defects in LPV systems, developed by recent work. The proposed methodology is illustrated with the results of simulations.
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