Fig. 1: Problem and Experiment Setup. | npj Robotics

Fig. 1: Problem and Experiment Setup.

From: FALCON: Fourier Adaptive Learning and Control for Disturbance Rejection Under Extreme Turbulence

Fig. 1

A Complex airflow structures in urban environments. B The wing has 9 sensors to measure the airflow (8 equally spaced pressure taps and 1 pitot tube) and is mounted on a one-dimensional load cell to measure the lift. Trailing-edge flaps change orientation to manipulate the aerodynamic forces. C Experiment setup to create irregular turbulent wake of a bluff body under high wind speeds. D Smoke visualization of the turbulent wake of a cylinder at a smaller Reynolds number. This image is obtained at the Caltech Real Weather Wind Tunnel system at a significantly lower flow speed than the experiments conducted in this work for visualization purposes. The actual flow conditions used in our studies were too turbulent to have clear smoke visualization. E Under a uniform flow U, symmetric airfoils do not have any vertical aerodynamic forces on them when they are aligned with the airflow. However, altering the position of a trailing edge flap on the airfoil can modify the lift coefficient CL, yielding an upward or downward aerodynamic lift force. F Outline of FALCON, a model-based reinforcement learning framework that allows effective modeling and control of the aerodynamic forces due to turbulent flow dynamics and achieves state-of-the-art disturbance rejection performance.

Back to article page