Static Feedback Control Augmented with an Adaptive Neural Network Applied to an Aerospace Structure

For the purpose of controlling an aerospace structure, this paper discusses a controller architecture which is comprised of a static gain feedback controller, augmented with a neural network adaptive controller. A typical approach to constructing an aerospace system controller is to schedule a set of static gains, depending upon selective operating conditions. A shortcoming of this approach is ensuring robustness across the entire operating envelope and to uncertainties in the system. To overcome this issue, an adaptive controller is incorporated into the architecture. The adaptive controller acts to improve the rapidity and robustness of the static gain feedback controller. This architecture is applied to suppressing unstable wing oscillations, and demonstrated through Monte Carlo analysis.