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This work presents a novel motor-level Nonlinear Model Predictive Control trajectory tracking controller for an over-actuated quadrotor with tilting propellers. The proposed controller directly provides the motor-level commands for both the tilting and the spinning of the propellers. Moreover, it optimally solves the control allocation problem arising from the system’s over-actuation taking into account the physical constraints of the platform. Leveraging a look-ahead strategy combined with the knowledge of the actuation limits, the proposed solution fully exploits the vehicle capabilities and accurately tracks the desired reference. Simulation results show that the solution proposed outperforms a state-of-the-art controller based on Feedback Linearization, in terms of both trajectory tracking and robustness to unmodeled dynamics.

A control strategy consisting of a feedforward action and a robust feedback for a gate automation is presented, where a low-cost and non-regenerative motor drive is used. A model of the system is developed and feedback linearization is used to compensate for the highly nonlinear dynamics of the electric drive. To achieve good motion tracking performance we design a smooth reference associated with a feedforward action, based on the nominal model of the system. In addition, based on a model of the uncertainties a robust feedback controller is tuned by solving a set of linear matrix inequalities, combining the optimization of a LQR cost with some pole placement constraints. Finally, we test the proposed control strategy on an experimental device, obtaining satisfactory results.

We consider the hovering control problem for a class of multi-rotor aerial platforms with generically oriented propellers. Given the intrinsically coupled translational and rotational dynamics of such vehicles, we first discuss some assumptions for the considered systems to reject moment disturbances and to balance the gravity force, which are translated into a geometric characterization of the platforms that is usually fulfilled by both standard models and more general configurations. Hence, we propose a control strategy based on the identification of a zero-moment direction for the applied force and the dynamic state feedback linearization around this preferential direction, which allows to asymptotically stabilize the platform to a static hovering condition. Stability and convergence properties of the control law are rigorously proved through Lyapunov-based methods and reduction theorems for the stability of nested sets. Asymptotic zeroing of the error dynamics and convergence to the static hovering condition are then confirmed by simulation results on a star-shaped hexarotor model with tilted propellers.