Quad-planes combine hovering and vertical takeoff and landing capability with fast and efficient forward flight. Regular Quad-planes with dedicated pusher motor can be subject to gust disturbances, and are not well-equipped to deal with actuator faults. Dual-axis Tilt-Rotor quad-planes are more maneuverable due to their overactuation. This also increases their gust resilience and allows them to hover statically after actuator failures. The vehicle in this paper uses an Incremental Nonlinear Dynamic Inversion (INDI ) controller, combined with a nonlinear Sequential Quadratic Programming (SQP) Control Allocation (CA ) algorithm, which can also find hover solutions in the case of actuator failures. We investigate both a combined allocation of linear and angular accelerations, as well as a cascaded allocation scheme. Due to large required changes in roll and pitch angles, the cascaded approach is selected in this research. Introduction of a tertiary control effort term, separation of attitude and actuator command optimization and a simulated Fault Detection and Identification ( FDI) mechanism led to repeated successful recovery from a motor failure in hover. Position tracking was demonstrated under failure in the recon- figured flight condition. Index Terms- Tilt-rotor, dual-axis tilt, quad-plane, FTC, over- actuated, control allocation

This paper proposes a control strategy based on incremental nonlinear dynamic inversion (INDI), meant for trajectory tracking purposes. The controller extends the conven- tional capabilities of INDI by including actuator dynamics in the inversion law and introducing a state dependent compensation term to reduce the effort of the error controller. A complementary filter is employed to reduce the degrading effect introduced by the filtering-induced delay in the feedback loop. Both simulated and real flight tests are conducted on a quadrotor configuration with artificially slowed down actuators and a drag plate mounted on top, to better observe the effect of actuator dynamics and state dependent dynamics in trajectory tracking accuracy. Simulations show that the combination of the two additional features increases tracking accuracy both in the short and long term response. It is also found that an overestimation of the state compensation term leads to instability, which makes the strategy not robust to model mismatch. Real flight tests, involving the tracking of a series of doublets on the pitch attitude and a lemniscate of Bernoulli, show that, as the complexity of the maneuver increases, the less the state compensation term effectively contributes to an improved tracking when the model is incomplete. On the other hand, trajectory tracking accuracy due to the consideration of actuator dynamics shows consistency and improvement respect to conventional INDI solutions.