Parameter identification with a controlled free flying model of a spaceplane

Kirschstein, Stefan; Alles, Wolfgang

doi:10.1016/j.ast.2005.03.001

Cited by 6 publications

(2 citation statements)

References 3 publications

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“…American Flight Dynamics Group AGARD established a special team named FMP WG18 in 1987, whose task is to carry out the research on system identification methods and application of rotor aircraft [2]. In the past ten years, a large number of researches on the helicopter modeling, identification and control have been studied abroad and have obtained different degree of progresses [3,4]. Meanwhile, some achievements in the study of helicopter modeling and parameter identification method have also obtained in China [5,6].…”

Section: Introductionmentioning

confidence: 99%

Helicopter Aerodynamic Parameter Identification via Flight Dynamics

Zhao

2013

AMM

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A method which can process flight test data by integrating parameter identification and non-dimensional flight dynamic model was proposed to acquire the effective aerodynamic parameters of a helicopter. First of all, a non-dimensional mathematic model considering flight dynamics was deduced for a helicopter in state of level flight, and some important parameters including aerodynamic and correctional were developed. Next, taking helicopter Z-9× for example, the least squares method was adopted to identify these parameters based actual flight test data. Lastly, the identification method was proved valid through feasibility analysis. Results show that this method is a good way to acquire aerodynamic parameters and can shorten flight test periods as well.

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Section: Introductionmentioning

confidence: 99%

Helicopter Aerodynamic Parameter Identification via Flight Dynamics

Zhao

2013

AMM

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“…In this field, estimation of the vehicle physical characteristics such as aerodynamic coefficients, flight derivatives, natural frequency, and, etc. have been separately done in the previous works (Kirschstein and Alles, 2005; Fullekrug and Sinapius, 1998). A particular form of the system equations that has been used with enormous success in aerospace applications is the linearized model.…”

Section: Introductionmentioning

confidence: 99%

On estimation of vehicle linear model parameters

Tayefi

Roshanian²,

Ghaffari³

2009

Aircraft Engineering and Aerospace Technology

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PurposeThe purpose of this paper is to identify linear model parameters of launch vehicles based on the actual flight test data. To compare the estimated parameters with the ones obtained by two other approaches: identification based on the recorded data from six‐degree‐freedom simulation of motion and linearization of the equations of motion via small‐disturbance theory as an analytical method.Design/methodology/approachAs the vehicle contains all the key issues in system identification such as time‐varying, unstable, nonlinear, and closed‐loop dynamics, Kalman filter method under the autoregressive with exogenous input model structure is used as a powerful method to estimate the dynamic parameters.FindingsSimulation results demonstrate that the linear model parameters used in the vehicle design and analysis should be validated by flight test data to accurate the vehicle dynamic model as more as possible.Practical implicationsOne of the most important usages of a linear model of aerospace vehicles is to design their controller. Another application of the algorithm presented in this paper is to estimate online dynamic parameters of the vehicle when they are required for the operation of the control system.Originality/valueBeing strongly affected by vehicle dynamic characteristics, linear model parameters of launch vehicles play important part in their design and analysis.

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