CERESResearch Repository

Nonlinear model predictive control for hybrid flapping-rotor micro aerial vehicles

Loading...
Thumbnail Image

Date published

Free to read from

2026-07-21

Supervisor/s

Industry supervisor/s

Journal Title

Journal ISSN

Volume Title

Department

Course name

ISSN

0731-5090

Format

Citation

Huang X, Lu L, Whidborne J, Pavel M. (2026) Nonlinear model predictive control for hybrid flapping-rotor micro aerial vehicles. Journal of Guidance, Control, and Dynamics, Available online 31 May 2026

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.

Description

Software description

Software language

Git repository

Keywords

Unmanned Aerial Vehicle, Nonlinear Model Predictive Control, Flight Testing, Attitude Stabilization, Aircraft Wing Design, Rotary Wing Aircraft, Aerodynamic Performance, Model Predictive Control, Micro Aerial Vehicles, Flapping-Wing Rotor, 4012 Fluid Mechanics and Thermal Engineering, 40 Engineering, 7 Affordable and Clean Energy, Aerospace & Aeronautics, 4001 Aerospace engineering, 4007 Control engineering, mechatronics and robotics, 4017 Mechanical engineering

DOI

Rights

Attribution 4.0 International

Funder/s

Grant number

Relationships

Relationships

Resources