Learning-based Adaptive Gust Mitigation with Oscillating Wings

Abstract

This paper investigates the application of a learning-based adaptive controller to mitigate the effect of gust on the lift generated by an airfoil in an unsteady flow environment. A high-order accurate CFD model is used to model the unsteady flow over a pitching airfoil. Open-loop simulations of the CFD model are used to ascertain feasible lift commands. The learning-based adaptive controller is based on the retrospective cost adaptive control (RCAC). First, RCAC is used to regulate the lift coefficient of the airfoil in a nominal case without gust. Next, the effect of the hyperparameters of the adaptive control on the closed-loop performance is investigated. Finally, we used RCAC to regulate the lift coefficient and mitigated the effect of gust on the airfoil.

Adaptive Combustion Regulation in Solid Fuel Ramjet

“…where the regressor matrix Φ 𝑘 contains the measured data and the controller gain vector 𝜃 𝑘 is optimized by the RCAC algorithm described in [32,33]. Finally, the heat flux 𝑤 𝑘 is the output of a nonlinear map and is given by…”