This paper presents a method for identifying flight dynamics models for aircraft that includes effects from the flexible structure and the effects from unsteady aerodynamics. In the time domain, the unsteady aerodynamic effects are often modelled using aerodynamic lag states. The proposed method involves first determining the poles that govern the dynamics for these lag states from flight data. This is followed by reconstructing the time signal histories for these lag states so that they can then be used as part of the model fitting procedure. Flight tests were conducted using a scaled Diana2 glider unmanned aerial vehicle (UAV) in order to collect experimental data for modelling. To be able to measure the response of the aircraft and its structure, the glider was instrumented with a wide range of sensors including accelerometers, gyroscopes and strain gauges placed across the aircraft structure. During the flight, various excitation manoeuvres were conducted by the pilot while the aircraft responses were collected. From these measurements, a full flight dynamics model consisting of both lateral and longitudinal dynamics was then identified. Additionally, a model predicting the tail and wing root loads was also identified. First, a rigid aircraft model was fitted that was then extended with states corresponding to the flexible modes and aerodynamic lags. Comparison between the rigid and extended model showed that the addition of structural modes and aerodynamic lag states to the identified models can lead up to 30% improvement in predicting aircraft responses. In conclusion, the method developed and presented in this paper is able to identify flight dynamics models from flight data that more accurately capture the dynamics of flexible aircraft by including effects from the flexible structure and unsteady aerodynamics. @en

This paper proposes an extension to the traditional flight path reconstruction filter to simultaneously reconstruct the aircraft rigid body states together with modal amplitudes and velocities of the structure. To achieve this, the filter makes use of additional accelerometers, gyroscopes and strain gauges placed across the aircraft structure. These measurements are used in a Kalman filter together with kinematic equations of a flexible aircraft and structural mode shapes. First a simulation model is used to evaluate the filter performance on reference signals where the true state is known. Finally, flight test measurements obtained using an instrumented Diana 2 scaled glider are used to validate the filter.@en

A ground vibration test was conducted with a 1:3 scaled Diana 2 glider model where the modal parameters were estimated using the accelerometers, gyroscopes and strain gauges integrated in the test aircraft and validated using externally attached calibrated accelerometers and commercial software. These modal parameters were then used to update a FEM model of the glider together with static load tests and component mass measurements. The goal for this updated and fitted FEM model is then to build an aeroelastic model for flexible aircraft flight dynamics simulator.

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Netherlands Aerospace Centre (NLR) and Delft University of Technology (TUD) have obtained an unmanned aerial vehicle to serve as a test platform for future aeroservoelastic flight testing. The purpose of this testbed is to collect data about flexible aircraft flight dynamic responses and loads on the aircraft at unsteady airflow conditions for flexible aircraft system identification. An overview of the 1:3 scaled Diana 2 glider is presented together with numerous tests that were conducted to characterise the test platform. Moment of inertia of the aircraft was determined using a pendulum and rotational swing setup, control surface dynamics were identified from sine sweeps and the structural modes and frequencies were obtained from a ground vibration test. Finally, a low cost and modular data acquisition system was built to collect all the sensor measurements. This data acquisition system is presented together with an overview of its performance.@en