Height Estimation and Control of Rotorcraft in Ground Effect Using Spatially Distributed Pressure Sensing

We describe a dynamic height controller for rotorcraft hovering and landing in ground effect based on flow field sensing and estimation. The rotor downwash in ground effect is represented using a ring-source potential-flow model selected for real-time use and validated experimentally. A nonlinear dynamic model of the heave test stand that represents the dynamics of a rotorcraft in ground effect is presented. Flow field pressure measurements are compared with flow-model predictions in a grid-based recursive Bayesian filter to estimate height above ground. Height control in ground effect using the estimated height is implemented with a dynamic linear controller. The experimental results show that height estimation and control are possible for a miniature autonomous rotorcraft by comparing two sets of differential pressure measurements in the rotor downwash with a low-order aerodynamic model in a Bayesian filter.