A New Formulation of the Filter-Error Method for Aerodynamic Parameter Estimation in Turbulence
Author(s) -
Jared A. Grauer,
Eugene A. Morelli
Publication year - 2015
Publication title -
aiaa atmospheric flight mechanics conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2015-2704
Subject(s) - aerodynamics , turbulence , computer science , filter (signal processing) , estimation theory , control theory (sociology) , algorithm , engineering , artificial intelligence , physics , aerospace engineering , mechanics , control (management) , computer vision
A new formulation of the filter-error method for estimating aerodynamic parameters in nonlinear aircraft dynamic models during turbulence was developed and demonstrated. The approach uses an estimate of the measurement noise covariance to identify the model parameters, their uncertainties, and the process noise covariance, in a relaxation method analogous to the output-error method. Prior information on the model parameters and uncertainties can be supplied, and a post-estimation correction to the uncertainty was included to account for colored residuals not considered in the theory. No tuning parameters, needing adjustment by the analyst, are used in the estimation. The method was demonstrated in simulation using the NASA Generic Transport Model, then applied to the subscale T-2 jet-engine transport aircraft flight. Modeling results in different levels of turbulence were compared with results from time-domain output error and frequency- domain equation error methods to demonstrate the effectiveness of the approach.
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