Model Predictive Control (MPC) is a candidate solution to aggressively control a constrained plant. In Tube Model Predictive Control (TMPC), optimality is traded for robustness which is a key aspect in flight controls where the plant is subject to many disturbances and uncertainties especially related to aerodynamics and wind. Yet MPC comes with large computational effort and thus reduced execution rates of the control law which aggravates disturbance rejection. This issue can be addressed by executing optimization-based feedforward and simple feedback control at different rates. Therefore, the authors present a complete workflow for multi-rate control design, soft- and hardware implementation, testing and flight experiment conduction. First, the control laws are discussed. Next, the custom onboard control software is presented and benchmarked in a tailored Hardware-in-the-Loop (HIL) simulation. Finally, flight experiments demonstrate the performance of the TMPC and the ease of design, implementation and testing entailed by the presented approach.      «

Model Predictive Control (MPC) is a candidate solution to aggressively control a constrained plant. In Tube Model Predictive Control (TMPC), optimality is traded for robustness which is a key aspect in flight controls where the plant is subject to many disturbances and uncertainties especially related to aerodynamics and wind. Yet MPC comes with large computational effort and thus reduced execution rates of the control law which aggravates disturbance rejection. This issue can be addressed by ex...     »