Implementation of Nonlinear Reconfigurable Controllers for Autonomous Unmanned Vehicles

Reconfigurable control will play a major role in the advancement of aerospace control especially in the realm of autonomous air vehicles. This paper consists of the development and future implementation of three nonlinear controllers. A modified dynamic inversion controller will be used for validation of the flight hardware. A Single Network Adaptive Critic (SNAC) controller will then be implemented to test its viability and robustness. Lastly, an outer loop controller in the form of an online learning neural network will be developed and implemented to supply extra control to the actual aircraft if a change in system dynamics is detected. To aid in system identification, parameter estimation will be performed before any autonomous flights are performed. The results of this project will validate the use of a SNAC controller for autonomous flight as well as prove the viability of an outer loop extra controller to account for changes in system dynamics