Nonlinear Model Predictive Control for Hybrid Flapping-Rotor Micro Aerial Vehicles

Abstract

To enhance the aerodynamic efficiency of micro aerial vehicles (MAVs) with rotary wings, a bio-inspired hybrid flapping-wing rotor (HFWR) configuration can be designed that achieves a power efficiency more than twice that of conventional rotors. Nevertheless, up to the present, the controllable flight of HFWR has so far eluded realization due to severe flapping-induced structural vibrations and nonlinear coupling between aerodynamic and elastic dynamics. This paper provides a practical step toward stable, controllable HFWR flight through two key innovations: a thrust-vectoring gimbal architecture that delivers continuous control moments under strong oscillations, and an enhanced nonlinear model predictive control (E-MPC) framework implemented as a distributed two-layer architecture. In this architecture, the outer layer consists of a lower-rate offboard MPC that generates constraint-aware attitude trim and bias commands, while the inner layer is a high-rate onboard proportional angular-rate loop that provides rapid damping of high-frequency perturbations caused by flapping-induced vibrations and communication or optimization latency. Hover and yaw flight tests demonstrate that the integrated architecture improves attitude stability compared with cascade PID and a baseline offboard MPC without the onboard rate loop, reducing peak deviation, overshoot, and steady-state error by up to 83%, 92%, and 80%, respectively, while substantially lowering control energy. These results demonstrate a practical pathway toward stable control of flapping-rotor MAVs for the first time, bridging the gap between bio-inspired aerodynamic efficiency and flight controllability.