Nonlinear Model Predictive Control combined with Geometric Attitude and Speed Control for Fixed-Wing UAVs

We propose the combination of a Nonlinear Model Predictive Controller (NMPC) with a Geometric Controller (GC) for the attitude and speed control problem of fixed-wing unmanned aerial vehicles (UAVs). The NMPC sends reference vectors for attitude, angular rates and angular acceleration to the low-level GC that can be run at a significantly higher bandwidth. This way we generate optimal references for the GC, increase its region of attraction while also addressing performance and constraint satisfaction. The efficacy of the proposed approach is illustrated in numerical simulation examples.