Active maneuver load alleviation for a pitching wing via spanwise-distributed camber morphing

This paper presents the design and verification of a nonlinear model inversion (NMI) controller for the maneuver load alleviation of a pitching oscillating wing based on spanwise-distributed active camber morphing. Recurrent neural networks (RNNs) are used to predict nonlinear and unsteady aerodynamic forces due to wing's large amplitude pitching maneuver, and a fully connected neural network is introduced to build the dynamic inversion of the aeroelastic system for control law design. The inversed system is concatenated with a PI controller to assemble a nonlinear active controller. The controller is first utilized in an offline environment for a 1DoF pitching finite-span wing with spanwise-distributed active camber morphing and then verified in CFD-based fluid-structure-control coupling simulation. The results show that the offline controller could eliminate the maneuver load. In the online CFD-based fluid-structure-control simulation, the bending moment can be alleviated by 38%.