Abstract
Abstract We propose the design of a nonlinear model predictive controller (NMPC) for the attitude and speed control problem of fixed-wing unmanned aerial vehicles (UAVs). The controller is designed to stabilize to a set-point in the output space that allows for a globally unique minimum of a quadratic cost for either roll-pitch or pitch-yaw control. The applicability of the proposed method is illustrated with numerical results where we show that even for initial conditions far from the reference, high update rates are feasible on off-the-shelf single-board computers which can be embedded in the UAVs flight stack.
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