The development of flight control systems for aerospace vehicles requires the availability of reliable aerodynamic models. Pre-flight models, obtained by means of wind tunnel tests and computational fluid dynamics analyses, are usually to be refined using test flight data in order to reduce the level of uncertainty on aerodynamic coefficients. In this paper we present a methodology for the estimation of the lateral-directional aerodynamic model of a re-entry vehicle in subsonic, transonic and supersonic regimes. The identification is formulated as a nonlinear filtering problem and solved through a multi-step approach using the Unscented Kalman Filter. The exploitation of all the available a priori information for the stochastic characterization of the filter models and sensors noises and a rigorous management of all the uncertainties involved in the system identification process allow to obtain reliable figures of estimation accuracy, that are of paramount importance for the design of guidance, navigation and control (GNC) system. The methodology is applied to the simulated data of the CIRA Dropped Transonic Flight Test 2 mission, that will be performed by the end of 2009, with the objective of refining the lateral-directional aerodynamic model. © 2009 IFAC.
Identification of the Transonic Aerodynamic Model for a Re--entry Vehicle / A., Vitale; F., Corraro; M., Bernard; DE MATTEIS, Guido. - ELETTRONICO. - 15:PART 1(2009), pp. 1211-1216. (Intervento presentato al convegno 15th IFAC Symposium on System Identification, SYSID 2009 tenutosi a Saint-Malo; France nel 6-8 Luglio 2009) [10.3182/20090706-3-FR-2004.00201].
Identification of the Transonic Aerodynamic Model for a Re--entry Vehicle
DE MATTEIS, GUIDO
2009
Abstract
The development of flight control systems for aerospace vehicles requires the availability of reliable aerodynamic models. Pre-flight models, obtained by means of wind tunnel tests and computational fluid dynamics analyses, are usually to be refined using test flight data in order to reduce the level of uncertainty on aerodynamic coefficients. In this paper we present a methodology for the estimation of the lateral-directional aerodynamic model of a re-entry vehicle in subsonic, transonic and supersonic regimes. The identification is formulated as a nonlinear filtering problem and solved through a multi-step approach using the Unscented Kalman Filter. The exploitation of all the available a priori information for the stochastic characterization of the filter models and sensors noises and a rigorous management of all the uncertainties involved in the system identification process allow to obtain reliable figures of estimation accuracy, that are of paramount importance for the design of guidance, navigation and control (GNC) system. The methodology is applied to the simulated data of the CIRA Dropped Transonic Flight Test 2 mission, that will be performed by the end of 2009, with the objective of refining the lateral-directional aerodynamic model. © 2009 IFAC.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.