Tube-based Robust MPC Processor-In-the-Loop Validation for Fixed-Wing UAVs

Real systems, as Unmanned Aerial Vehicles (UAVs), are usually subject to environmental disturbances, which could compromise the mission accomplishment. For this reason, the main idea proposed in this research is the design of a robust controller, as autopilot control system candidate for a fixedwing UAV. In detail, the inner loop of the autopilot system is designed with a tube-based robust model predictive control (TRMPC) scheme, able to handle additive noise. Moreover, the navigation outer loop is regulated by a proportional-integralderivative controller. The proposed TRMPC is composed of two parts: (i) a linear nominal dynamics, evaluated online with an optimization problem, and (ii) a linear error dynamics, which includes a feedback gain matrix, evaluated offline. The key aspects of the proposed methodology are: (i) offline evaluation of the feedback gain matrix, and (ii) robustness to random, bounded disturbances. Moreover, a path-following algorithm is designated for the guidance task, which provides the reference heading angle as input to the control algorithm. Software-in-theloop and processor-in-the-loop simulations have been performed to validate the proposed approach. The obtained performance have been evaluated in terms of tracking capabilities and computational load, assessing the real-time implementability compliance with the XMOS development board, selected as continuation of previous works.