Digital Autoland Control Laws Using Quantitative Feedback Theory and Direct Digital Design

of several aircraft problems, but not for outer-loop control or for automatic landing. This paper describes the synthesis and development of an automatic landing controller for medium-sized unmanned aerial vehicles, using discrete quantitative feedback theory. Controllers for the localizer, glideslope tracker, and automatic flare are developed, with a focus on outer-loop synthesis and robustness with respect to model uncertainty. Linear, nonreal-time, six-degree-of-freedom Monte Carlo simulation is used to compare the quantitative feedback theory controller with a baseline proportional–integral controller in several still-air and turbulent-air landing scenarios. Results presented in the paper show that the quantitative feedback theory controller provides superior performance robustness to the proportional–integral controller in turbulent-air conditions when model uncertainties are present. It is therefore concluded to be a promising candidate for an autoland controller for unmanned air vehicles.