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A generalized Frame Adaptive MPC for the low-level control of UAVs

The aim of this article is to establish an adaptive Model Predictive Control (MPC) scheme for the angular rate and thrust control of a multirotor Unmanned Aerial Vehicle (UAV). The proposed model adaptiveness comes from estimating the movement of the Center of Gravity CoG combined with the thrust constant of the motors, making the system robust to disturbances and fast to adapt to changing parameters, while also taking under consideration the control signal bounds in order to guarantee for no motor stalls, while flying. The linear requirements of the MPC are adhered to by transforming the estimation and control problem into a control signal squared domain, making the system linear. The efficacy of the proposed estimation and control scheme is presented in simulations where worst case scenarios have been considered.