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

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.

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Publication Details

Journal
Journal of Guidance Control and Dynamics
Published
2026-05-31
DOI
https://doi.org/10.2514/1.g009744
Primary Topic
Biomimetic flight and propulsion mechanisms
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Linghai Lu, Xun Huang, Marilena Pavel, James Whidborne
Journal of Guidance Control and Dynamics
Biomimetic flight and propulsion mechanisms
article

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

Linghai Lu, Xun Huang, Marilena Pavel, James Whidborne
article en

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.

Journal of Guidance Control and Dynamics
Cranfield University (GB), Delft University of Technology (NL)
Affordable and clean energy
Openalex Percentile: Top 2%
Biomimetic flight and propulsion mechanisms
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