Unscented Kalman Filter for Fault Detection
| Authors: | Xiong Kai, Beihang University, China
Chan C. W., The University of Hong Kong, China
Zhang H. Y., Beihang University, China |
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| Topic: | 6.4 Safeprocess |
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| Session: | Fault Detection and Isolation for Nonlinear Systems |
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| Keywords: | fault detection, nonlinear filters, extended Kalman filters, unscented transformation, satellite attitude sensors |
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Abstract
In this paper, the approximation of nonlinear systems using unscented Kalman filter (UKF) is discussed, and the conditions for the convergence of the UKF are derived. The detection of faults from residuals generated by the UKF is presented. As fault detection often reduced to detecting irregularities in the residuals, such as the mean, the local approach, a powerful statistical technique to detect such changes, is used to detect fault from the residuals generated from the UKF. The properties of the proposed method are also presented. To illustrate the performance of the proposed method, it is applied to detect faults in the attitude sensors of a satellite.
