Sensor Fault Detection and Diagnosis of a Process Using Unknown Input Observer
AbstractIn this paper, a robust sensor fault detection and isolation (FDI) method based on the unknown input observer (UIO) approach is presented. The basic principle of unknown input observers is to decouple disturbances from the state estimation error. A single full-order observer is designed to detect sensor faults in the presence of unknown inputs (disturbances). By doing so, we generate a residual, a weighted output of the state estimation error, decoupled from disturbances. The resulting robust (in the sense of disturbances) residual can be used for fault detection. Although this scheme has successful fault detection, using one observer is not successful in fault isolation. Therefore, a robust sensor fault isolation observer scheme is proposed. In order to evaluate its ability, the presented method is adopted to detect and isolate sensor faults of a highly nonlinear dynamic system. The faulty behavior of output sensors in a jacketed continuous stirred tank reactor (CSTR), around operating point, is investigated. Simulation results show that model uncertainties and disturbances can be distinguished from a response to a sensor fault.
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Zarei, J.; Poshtan, J. Sensor Fault Detection and Diagnosis of a Process Using Unknown Input Observer. Math. Comput. Appl. 2011, 16, 31-42.
Zarei J, Poshtan J. Sensor Fault Detection and Diagnosis of a Process Using Unknown Input Observer. Mathematical and Computational Applications. 2011; 16(1):31-42.Chicago/Turabian Style
Zarei, Jafar; Poshtan, Javad. 2011. "Sensor Fault Detection and Diagnosis of a Process Using Unknown Input Observer." Math. Comput. Appl. 16, no. 1: 31-42.