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Determination of Airplane Model Structure From Flight Data by Using Modified Stepwise Regression
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In this paper, the problem of determining airplane model structure is addressed using linear and stepwise regressions, and the MSR was constructed to force a linear model for the aerodynamic coefficient first, then add significant nonlinear terms and delete nonsignificant terms from the model.Abstract:
The linear and stepwise regressions are briefly introduced, then the problem of determining airplane model structure is addressed. The MSR was constructed to force a linear model for the aerodynamic coefficient first, then add significant nonlinear terms and delete nonsignificant terms from the model. In addition to the statistical criteria in the stepwise regression, the prediction sum of squares (PRESS) criterion and the analysis of residuals were examined for the selection of an adequate model. The procedure is used in examples with simulated and real flight data. It is shown that the MSR performs better than the ordinary stepwise regression and that the technique can also be applied to the large amplitude maneuvers.read more
Citations
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Aircraft flight characteristics in icing conditions
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Nonlinear aerodynamic modeling using multivariate orthogonal functions
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References
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Norman R. Draper,Harry Smith +1 more
TL;DR: In this article, the Straight Line Case is used to fit a straight line by least squares, and the Durbin-Watson Test is used for checking the straight line fit.
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Heinz Unbehauen,B. Göhring +1 more
TL;DR: In this article, the accuracy of the models estimated with the direct least squares-and maximum likelihood-methods is investigated critically, in order to determine also the most accurate order of the model, seven structure testing methods are thoroughly investigated.
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George E. P. Box,John Wetz +1 more
TL;DR: In this paper, a measure of the discrepancy introduced due to the bias term beta in relation to the error of estimate of the response is proposed, and the interpolation efficiency is defined.
Maximum likelihood identification and optimal input design for identifying aircraft stability and control derivatives
D. E. Stepner,Raman K. Mehra +1 more
TL;DR: In this paper, a new method of extracting aircraft stability and control derivatives from flight test data is developed based on the maximum likelihood cirterion, which is capable of processing data from both linear and nonlinear models, both with and without process noise.