Reconfiguration strategy for a DC-DC boost converter using sliding mode observers and fault identification with a neural network
Keywords: DC-DC converters, sensor faults, sliding mode control, sliding mode observer, pattern recognition
AbstractIn this paper, a method for the reconfiguration of the operation of DC-DC boost converters is proposed using sliding mode observers (SMOs). Open sensor and high gain faults are analyzed. In the fault identification algorithm, a neural network with pattern recognition is proposed. The reconfiguration strategy consists in two auxiliary sliding mode state observers to estimate sensor values in the presence of faults, in order to guarantee a proper switching control law to keep the system stable.