Data-driven fault diagnosis and robust control: Application to PEM fuel cell systems
Journal Article (2017)
International Journal of Robust and Nonlinear Control
Sánchez Peña, Ricardo
Bianchi, Fernando Daniel
A data-driven methodology that includes the unfalsified control concept in the framework of fault diagnosis and isolation (FDI) and fault-tolerant control (FTC) is presented. The selection of the appropriate controller from a bank of controllers in a switching supervisory control setting is performed by using an adequate FDI outcome. By combining simultaneous on-line performance assessment of multiple controllers with the fault diagnosis decision from structured hypothesis tests (SHT), a diagnosis statement regarding what controller is most suitable to deal with the current (nominal or faulty) mode of the plant is obtained. Switching strategies that use the diagnosis statement are also proposed. This approach is applied to a non-linear experimentally validated model of the breathing system of a polymer electrolyte membrane (PEM) fuel cell. The results show the effectiveness of this FDI-FTC data-driven methodology.
adaptive control, automation, control theory, two-term control.
Fault diagnosis; fault-tolerant control; unfalsified control; fuel cells
C. Ocampo-Martínez, R. Sánchez-Peña, F. Bianchi and A. Ingimundarson. Data-driven fault diagnosis and robust control: Application to PEM fuel cell systems. International Journal of Robust and Nonlinear Control, 2017, to appear.