Abstract
When the observed input-output data are corrupted by the observed noises in the aircraft flutter stochastic model, we need to obtain the more exact aircraft flutter model parameters to predict the flutter boundary accuracy and assure flight safety. So, here we combine the instrumental variable method in system identification theory and variance matching in modern spectrum theory to propose a new identification strategy: instrumental variable variance method. In the aircraft flutter stochastic model, after introducing instrumental variable to develop a covariance function, a new criterion function, composed by a difference between the theory value and actual estimation value of the covariance function, is established. Now, the new criterion function based on the covariance function can be used to identify the unknown parameter vector in the transfer function form. Finally, we apply this new instrumental variable variance method to identify the transfer function in one electrical current loop of flight simulator and aircraft flutter model parameters. Several simulation experiments have been performed to demonstrate the effectiveness of the algorithm proposed in this paper.
Highlights
Flutter is a large-scale vibration phenomenon in which an elastic structure is coupled by aerodynamics, elastic force, and inertial force in a uniform airflow
In order to avoid the occurrence of flutter accidents, the new aircraft development must undergo one flutter test to determine the stable flight envelope without flight flutter. e main content of the flutter test is to apply excitation to the aircraft structure under different flight conditions and to identify the model parameters such as the flutter frequency and damping of the aeroelastic structure based on the dynamic response data
Based on the aforementioned research results, this paper continues to study the problem of identifying aircraft flutter model parameters in [12]. e main contribution of this paper is to combine instrumental variable method in system identification theory with variance matching method in modern spectrum estimation theory to form a new identification strategy—instrumental variable variance method
Summary
Flutter is a large-scale vibration phenomenon in which an elastic structure is coupled by aerodynamics, elastic force, and inertial force in a uniform airflow. E main content of the flutter test is to apply excitation to the aircraft structure under different flight conditions (different flight altitudes and speeds) and to identify the model parameters such as the flutter frequency and damping of the aeroelastic structure based on the dynamic response data. The instrumental variable and subspace identification algorithm are combined to obtain the optimal instrumental variable subspace identification algorithm, which is used to accurately identify each system matrix in the aircraft flutter stochastic model under the random statespace form, and the desired aircraft flutter model parameters are obtained. Based on the aforementioned research results, this paper continues to study the problem of identifying aircraft flutter model parameters in [12]. As accurate transfer function estimation is the premise of model parameter identification, the detailed process of minimizing the criterion function is deduced, and the corresponding partial derivative expression is given
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