Dual-layer optimization-based control allocation for a fixed-wing UAV

Many existing control allocation methods separate the high-level design from their low-level design, assuming that constraints of actuators can be guaranteed by allocator. This idea may not suitable for nonlinear fixed-wing unmanned aerial vehicle studied here, which hence motivates this work. In paper, we propose a new dual-layer optimization-based method, in proposed allocator, on one hand, modify pre-designed virtual signals when out-layer actuator, i.e., throttle, reaches its constraint. On other it reverts conventional constrained allocator throttle are inactive. Another feature is under framework, initial state augmented actuator dynamics serves as parameters, bringing more degrees freedom without affecting nominal stability. Apart paper also proposes flight controller based control-oriented model and combination dynamic inversion disturbance observer. Disturbance observer provides robustness estimating errors between true models, compensating them controller. High-fidelity simulation results realistic wind disturbances presented to demonstrate performance method.