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

Autoland controllers are prevalent for both large and small/micro unmanned aerial vehicles, but very few are available for medium-sized unmanned air vehicles. These vehicles tend to have limited sensors and instrumentation, yet must possess good performance in the presence of modeling uncertainties and exogenous inputs such as turbulence. Quantitative feedback theory has been reported in the literature for inner-loop control 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.