Volume 6, 2013Progress in Flight Dynamics, Guidance, Navigation, Control, Fault Detection, and Avionics
|Page(s)||299 - 316|
|Section||Fault detection and control|
|Published online||02 December 2013|
Model-based fault detection and identification with online aerodynamic model structure selection
German Aerospace Center DLR, Insititute of Robotics and Mechatronics 20 Münchner Straße, Weßling-Oberpfaffenhofen 82234, Germany
Delft University of Technology, Faculty of Aerospace Engineering 1 Kluyverweg, HS Delft 2629, the Netherlands
This publication describes a recursive algorithm for the approximation of time-varying nonlinear aerodynamic models by means of a joint adaptive selection of the model structure and parameter estimation. This procedure is called adaptive recursive orthogonal least squares (AROLS) and is an extension and modification of the previously developed ROLS procedure. This algorithm is particularly useful for model-based fault detection and identification (FDI) of aerospace systems. After the failure, a completely new aerodynamic model can be elaborated recursively with respect to structure as well as parameter values. The performance of the identification algorithm is demonstrated on a simulation data set.
© Owned by the authors, published by EDP Sciences, 2013
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 2.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.