Research Projects

The Fasel Lab studies how next-generation flight systems are designed and controlled to achieve greater efficiency, agility, and robustness. We combine scientific machine learning, control, and optimization to design and build such systems, with a central focus on integrating adaptive wing structures that can actively change shape and mechanical properties in flight.

Some particular research areas of interest and projects we are working on:

Robust sparse model discovery

Exploiting statistical methods to robustify the sparse identification of nonlinear dynamics (SINDy) algorithm

Data-driven control

Data-driven methods for model discovery and their application for nonlinear model predictive control.

Morphing wings

Aero-structural design and optimization of distributed compliance morphing wings.

Flapping wing micro aerial vehicles

Agile and computationally efficient trajectory tracking of sub-gram MAVs.

Data-driven aeroelastic reduced-order modeling

Data-driven modelling methods to develop highly accurate and tractable reduced-order aeroelastic models that are valid over a wide range of operating conditions and are suitable for control.

Concurrent wing design and flight mission optimization

System level power production optimization of airborne wind energy drones by concurrently optimizing the wing design and flight mission.

Composite structures

Design, optimization, and manufacturing of lightweight composite wing structures.

Renewable energy

Design, computational modeling, and optimization of airborne wind energy systems.