Robust Gust Load Alleviation at Different Flight Points and Mass configurations

Hugo Fournier (1) , Paolo Massioni (1) , Minh Tu Pham (1) , Laurent Bako (1) , Robin Vernay (2) , Michele Colombo (2)

1 AIS - Ampère, Département Automatique pour l'Ingénierie des Systèmes
2 Airbus [France]

This work studies the gust load alleviation of a flexible aircraft equipped with a lidar sensor that measures the wind velocity ahead of the aircraft. The focus is put on the aeroelastic dynamics uncertainties due to the evolution of the velocity and the altitude during a flight, and to the variations of the aircraft mass configuration. A robust control approach is adopted in order to minimize the aircraft loads due to the wind in presence of such uncertainties with low-order controllers that satisfy the constraints imposed by the system's limitations and the implementability considerations. This is achieved through structured mixed H-2/H-infinity synthesis with multiple models. The load alleviation capability of controllers of various orders, using a variable number of control surfaces, is assessed through the computation of the maximum loads obtained in various conditions of velocity, altitude and mass configurations.

Domaines: Automatique / Robotique

Hugo Fournier, Paolo Massioni, Minh Tu Pham, Laurent Bako, Robin Vernay, et al.. Robust Gust Load Alleviation at Different Flight Points and Mass configurations. AIAA SCITECH 2022 Forum, Jan 2022, San Diego, France. ⟨10.2514/6.2022-0285⟩. ⟨hal-03561621⟩