Assessing Sensor-Model-Fusion Technologies on a Flexible Aeroelastic Wing Demonstrator through Wind Tunnel Testing in the DLR Project SAFER²
Year: 2025
Type: conference-paper
Abstract: This study discusses the experimental exploration of novel sensor-model-fusion technologies on a flexible aeroelastic wing demonstrator through wind tunnel testing, as part of the DLR project SAFER2. The aeroelastic wing demonstrator is excited via inflow gusts and disturbances, generated by a gust rig, or using control surface deflections. A large variety of sensor systems are employed to capture these excitations and measure the loads, thereby enabling the effective testing of sensor-model-fusion technologies. Among the latter, active control methods to alleviate gust loads and to augment the wing damping, as well as an online-monitoring framework to identify structural modal parameters are explored. Two gust load alleviation strategies are investigated, which are either based on a robust control approach or leverage reinforcement learning techniques. The onlinemonitoring framework implements various operational modal analysis methods, coupling them with a linear Kalman filter. The damping augmentation controller uses a destabilization/stabilization approach, featuring a novel input-output blending method as well as a saturation mechanism to guarantee a safe operation. All sensor-model-fusion technologies tested yield promising results, whether these concern the effective reduction of gust-induced loads (e.g., wing-root bending moment), the accurate online monitoring of modal parameters, or the controlled destabilization and re-stabilization of the wing model using damping augmentation.
Source: elib (German Aerospace Center)
Authors: Schmidt, Thomas G., Volkmar, Robin, Micheli, Boris, Stalla, Julius Felix, Konatala, Ramesh, Hanke, Charlotte, Altkuckatz, Anna, Koida, Lukas, Braune, Marc, Soal, Keith Ian, Tang, Martin, Böswald, Marc, Dillinger, Johannes, Boose, Yannick, Mai, Holger
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7124515206
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