Adaptive Control of Unmanned Aerial Vehicles in Atmospheric Flight with Reduced Models

We propose an approximate implementation scheme for an adaptive linear quadratic control structure by employing a balanced truncation procedure in the loop prior to solving the associated Algebraic Riccati Equation (ARE). The control design combined with an adaptive law to compensate for uncertainties and possible changes in the dynamics is applied to the longitudinal model of an Unmanned Aerial Vehicle (UAV) in atmospheric flight. The tracking controllers based on the full and reduced order UAV models are constructed, and the resultant effect of the described model reduction on the flight performance of the vehicle is investigated through comparative simulations.