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Estimation of aircraft aerodynamic derivatives using Extended Kalman Filter

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dc.creator Curvo M.
dc.date 2000
dc.date.accessioned 2013-05-30T11:25:21Z
dc.date.available 2013-05-30T11:25:21Z
dc.date.issued 2013-05-30
dc.identifier http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-73862000000200001
dc.identifier http://www.doaj.org/doaj?func=openurl&genre=article&issn=01007386&date=2000&volume=22&issue=2&spage=133
dc.identifier.uri http://koha.mediu.edu.my:8181/jspui/handle/123456789/4585
dc.description Design of flight control laws, verification of performance predictions, and the implementation of flight simulations are tasks that require a mathematical model of the aircraft dynamics. The dynamical models are characterized by coefficients (aerodynamic derivatives) whose values must be determined from flight tests. This work outlines the use of the Extended Kalman Filter (EKF) in obtaining the aerodynamic derivatives of an aircraft. The EKF shows several advantages over the more traditional least-square method (LS). Among these the most important are: there are no restrictions on linearity or in the form which the parameters appears in the mathematical model describing the system, and it is not required that these parameters be time invariant. The EKF uses the statistical properties of the process and the observation noise, to produce estimates based on the mean square error of the estimates themselves. Differently, the LS minimizes a cost function based on the plant output behavior. Results for the estimation of some longitudinal aerodynamic derivatives from simulated data are presented.
dc.publisher The Brazilian Society of Mechanical Sciences
dc.source Journal of the Brazilian Society of Mechanical Sciences
dc.subject Aerodynamic Coefficient
dc.subject Aerodynamic Derivative
dc.subject Kalman Filter
dc.subject Parameter Estimation
dc.subject Simulation
dc.title Estimation of aircraft aerodynamic derivatives using Extended Kalman Filter

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