Data-driven fault diagnosis and robust control: application to PEM fuel cell systems

• Published in: International Journal of Robust and Nonlinear Control
• Main Authors: Ocampo Martínez, Carlos, Sanchez Peña, Ricardo Salvador, Bianchi, Fernando, Ingimundarson, Ari
• Format: Article in Journal/Newspaper
• Language: English
• Published: John Wiley & Sons Ltd
• Subjects: FAULT DIAGNOSIS; FAULT-TOLERANT CONTROL; FUEL CELLS; UNFALSIFIED CONTROL; https://purl.org/becyt/ford/2.2; https://purl.org/becyt/ford/2; Argentina; Martínez; Ricardo; Ari; Bianchi; Ocampo; Islandia
• Online Access: http://hdl.handle.net/11336/177014

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. Fil: Ocampo Martínez, Carlos. Universidad Politécnica de Catalunya. Departamento de Ingeniería de Sistemas, Automática e Informática Industrial; España Fil: Sanchez Peña, Ricardo Salvador. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Tecnológico de Buenos Aires; Argentina Fil: Bianchi, Fernando. Institut de Recerca de Energia de Catalunya; España Fil: Ingimundarson, Ari. Mannvit Hf; Islandia