Identification of dynamic derivatives with a controlled wind tunnel model of the spaceplane-configuration PHOENIX

Kirschstein, Stefan; Alles, Wolfgang

doi:10.1016/j.ast.2004.06.002

Cited by 3 publications

(5 citation statements)

References 3 publications

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“…To assure a rich spectrum, n prime number multiples of a base frequency must be used, in order to avoid multiples of the same base frequency at the same position in the spectrum, and each added sinusoidal signal must have a different phase. It guarantees the signal as being of order of persistency n. This signal has the disadvantages that its power decreases with the number of added sines and the estimated parameters can present high correlation [9].…”

Section: Input Signalsmentioning

confidence: 98%

Strategies for in-orbit calibration of drag-free control systems

Guilherme

Filho

Theil

2008

Aerospace Science and Technology

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Drag-Free Satellites (DFS) are a class of scientific satellite missions designed for research on fundamental physics as well as geodesy. They consist, basically, of a small inner satellite (test mass) located in a cavity inside a larger satellite, the normal one. The Drag-Free Attitude Control System (DFACS) is the most complex technology on-board these satellites. This key technology allows the residual accelerations on experiments on board the satellites to be significantly reduced. In order to achieve this very low disturbance environment (for some missions <10 −14 g) the drag-free control system has to be optimized. This optimization process is required because of uncertainties in system parameters that demand a robustness of the control system. This paper will present approaches for in-orbit calibration of drag-free control systems. The discussion includes modeling, with scale factors and cross couplings, possible excitation signals, comparison of different parameter identification/estimation methods as well as simulation results.

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Section: Input Signalsmentioning

confidence: 98%

Strategies for in-orbit calibration of drag-free control systems

Guilherme

Filho

Theil

2008

Aerospace Science and Technology

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“…As seen above, the linear quasi-static model does not take into account the dependence of the aerodynamic derivatives on unsteady aerodynamic effects. However, a variant of this method consists in adding a dynamic component to the coefficients in order to model these unsteady effects [4,17]. The expression of the unsteady longitudinal coefficients are presented below:…”

Section: Linear Unsteady Modelingmentioning

confidence: 99%

“…It consists of classical aerodynamic quasi-steady derivatives to which are added dynamic terms for the most signiőcant coefficients. These dynamic coefficients are solutions of a őrst order differential equation depending on the variation of the AOA [17]:…”

Section: Linear Unsteady Modelingmentioning

confidence: 99%

“…For a forced oscillation with a different frequency, the rotation rates and the hysteresis phenomena are changed. This leads to a dependence of the model coefficients on the frequency [10,17]. Therefore, the linear quasi-steady model does not take into account unsteady aerodynamic effects and it is not well suited for the analysis of a high performance aircraft with highly nonlinear and unsteady aerodynamics [13,18].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the linear quasi-steady model does not take into account unsteady aerodynamic effects and it is not well suited for the analysis of a high performance aircraft with highly nonlinear and unsteady aerodynamics [13,18]. This model can be improved in an linear unsteady model by adding a dynamic coefficient, solution of a differential equation, allowing to get away from this frequency dependence [4,17]. A non-linear model [10] can also be constructed.…”

Section: Introductionmentioning

confidence: 99%

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