17th AIAA Aerodynamic Decelerator Systems Technology Conference and Seminar 2003
DOI: 10.2514/6.2003-2118
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SPSA Algorithm for Parachute Parameter Estimation

Abstract: This paper presents an algorithm to estimate unknown parameters of parachute models from flight-test data. The algorithm is based on the simultaneous-perturbation-stochastic-approximation method to minimize the prediction error (difference between model output and test data). The algorithm is simple to code and requires only the model output. Analytical gradients are not necessary. The algorithm is used to estimate aerodynamic and apparent mass coefficients for an existing parachute model.

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“…For this problem to a considerable extent the values of ** l Φ depend on the accuracy of the experiment and physical sense of the proximity criteria (11). This brings us to the following formulation of multicriteria parameter identification problem for system (4) and sets of constraints (5), (6), and (12).…”
Section: From Multicriteria Optimization To Multicriteria Identifimentioning
confidence: 99%
“…For this problem to a considerable extent the values of ** l Φ depend on the accuracy of the experiment and physical sense of the proximity criteria (11). This brings us to the following formulation of multicriteria parameter identification problem for system (4) and sets of constraints (5), (6), and (12).…”
Section: From Multicriteria Optimization To Multicriteria Identifimentioning
confidence: 99%