Fault Detection and Identification of Actuator Faults using Linear Parameter Varying Models
| Authors: | Hallouzi Redouane, Delft University of Technology, Netherlands
Verdult Vincent, Delft University of Technology, Netherlands
Babuska Robert, Delft University of Technology, Netherlands
Verhaegen Michel, Delft University of Technology, Netherlands |
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| Topic: | 6.4 Safeprocess |
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| Session: | Fault Detection and Identification |
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| Keywords: | Fault detection and identification, LPV models, aircraft control, nonlinear systems |
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Abstract
A method is proposed to detect and identify two common classes ofactuator faults in nonlinear systems. The two fault classes aretotal and partial actuator faults. This is accomplished byrepresenting the nonlinear system by a Linear Parameter Varying(LPV) model, which is derived from experimental input-output data.The LPV model is used in a Kalman filter to estimate augmentedstates, which are directly related to the faults. Decision logichas been developed to determine the fault class from the estimatedaugmented states. The proposed method has been validated on anonlinear simulation model of a small commercial aircraft.
