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Math. Comput. Appl. 2011, 16(1), 31-42; doi:10.3390/mca16010031

Sensor Fault Detection and Diagnosis of a Process Using Unknown Input Observer

School of Electrical Engineering, Iran University of Science and Technology, Narmak 16846-13114, Tehran, Iran
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Published: 1 April 2011
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Abstract

In 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.
Keywords: Robust Fault Detection and Isolation; Unknown Input Observers, Disturbance decoupling Robust Fault Detection and Isolation; Unknown Input Observers, Disturbance decoupling
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Zarei, J.; Poshtan, J. Sensor Fault Detection and Diagnosis of a Process Using Unknown Input Observer. Math. Comput. Appl. 2011, 16, 31-42.

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