Data‐driven fault diagnosis and robust control: Application to PEM fuel cell systems

Summary 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...

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Bibliographic Details
Published in:International journal of robust and nonlinear control 2018-08, Vol.28 (12), p.3713-3727
Main Authors: Ocampo‐Martinez, Carlos, Sánchez‐Peña, Ricardo, Bianchi, Fernando, Ingimundarson, Ari
Format: Article
Language:English
Subjects:
adaptive control
automation
Automàtica i control
Classificació INSPEC
Control data (computers)
control theory
Controllers
Fault diagnosis
fault-tolerant control
Fuel cells
Informàtica
Performance assessment
Proton exchange membrane fuel cells
Robust control
Supervisory control
Switching
two-term control
unfalsified control
Àrees temàtiques de la UPC
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Summary:Summary 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 online performance assessment of multiple controllers with the fault diagnosis decision from structured hypothesis tests, 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 nonlinear experimentally validated model of the breathing system of a polymer electrolyte membrane fuel cell. The results show the effectiveness of this FDI–fault‐tolerant control data‐driven methodology. Copyright © 2017 John Wiley & Sons, Ltd.
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.3820