Norm-bounded model predictive control allocation strategy for an over-actuated aircraft

In this paper, a novel solution for addressing the control allocation problem for over-actuated unmanned aircraft is presented. In particular, a detailed High Altitude Performance Demonstrator (HAPD) is used to show the effectiveness of the control/allocation architecture. The novelty of the proposed solution consists of designing a model predictive controller compliant with input saturations, geometric constraints, model uncertainties and enjoying tracking capabilities to be used during the online operations to adapt the nominal allocation unit to the time-varying conditions arising from the nonlinear aircraft dynamics. To make this approach viable, the state trajectories of the nonlinear envelope are formally embedded into those pertaining to a norm-bounded linear description. Then the allocation task is addressed by defining an online reference generator in charge of providing a feasible reference trajectory compatible with timevarying flight conditions. Finally, the nominal allocation is adapted online by exploiting state prediction features of the model predictive controller. A simulation campaign, involving comparisons with a well-known competitor, is performed by enlightening the effectiveness of the proposed approach in fulfilling constraints, ensuring accurate trajectory tracking and optimally allocating the control effort.