Set-membership methodology for multiple fault detection and isolation in DC-DC Buck Converters

This paper addresses the problem of multiple Fault Detection and Isolation (FDI) in DC-DC Buck converters which are widely used in renewable energy systems. Under non-ideal conditions and the assumption that the model parameters uncertainties are bounded, set-membership FDI methodology is proposed....

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Bibliographic Details
Main Authors: El Houda Thabet, Rihab, Chafouk, Houcine
Format: Conference Proceeding
Language:English
Subjects:
Buck converters
Capacitors
Circuit faults
Conferences
DC-DC Converters
Electronics
Fault detection
Fault Isolation
Interval Predictors
Intervals
LPV systems
Mathematical model
Mathematical models
Methodology
MOSFET
Predictive models
Set-membership
Simulation
Uncertainty
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Summary:This paper addresses the problem of multiple Fault Detection and Isolation (FDI) in DC-DC Buck converters which are widely used in renewable energy systems. Under non-ideal conditions and the assumption that the model parameters uncertainties are bounded, set-membership FDI methodology is proposed. The approach relies on an interval predictor developed in [1] for Linear Parameter Varying (LPV) systems. This interval predictor is used in this work and applied to the proposed LPV form of a DC-DC Buck converter in order to detect and isolate multiple faults under noisy environment. A novel signal is proposed to ensure the purpose. The efficiency of the proposed methodology is illustrated through simulation results.
ISSN:2158-8481
DOI:10.1109/MELCON.2016.7495377