Nonlinear MPC with Motor Failure Identification and Recovery for Safe and Aggressive Multicopter Flight

Safe and precise reference tracking is a crucial characteristic of Micro Aerial Vehicles (MAVs) that have to operate under the influence of external disturbances in cluttered environments. In this paper, we present a Nonlinear Model Predictive Control (NMPC) that exploits the fully physics based non-linear dynamics of the system. We furthermore show how the moment and thrust control inputs can be transformed into feasible actuator commands. In order to guarantee safe operation despite potential loss of a motor under which we show our system keeps operating safely, we developed an Extended Kalman Filter (EKF) based motor failure identification algorithm. We verify the effectiveness of the developed pipeline in flight experiments with and without motor failures.