High-fidelity Model and Nonlinear Model Predictive Control for Flip Maneuvers of Tailless Flapping-Wing Robots

Insects and hummingbirds exhibit remarkable agility, including full body flip maneuvers. Achieving similar maneuvers of bio-inspired tailless flapping-wing robots (FWRs) is challenging due to the complex dynamics, inherent nonlinearities and control issues. This paper presents an nonlinear model predictive control (NMPC) algorithm to enable the 360-degree flip maneuver for the developed X-wing tailless FWR, which weighs 30.8 g and has a wingspan of 14.5 cm. We first introduce a high-fidelity model of the FWR, which incorporates the aerodynamics of the wings, dynamics of the motors and servos, body kinodynamic model, and the model of thrust and torques generation. This high-fidelity model allows for testing the FWR in simulation environments, thereby reducing the damage and cost associated with flip maneuvers in real-world experiments. Based on this high-fidelity model, we propose an NMPC controller to offline compute optimal state trajectories and corresponding control inputs, which are then used as state references and the feedforward control for the FWR during its 360-degree flip maneuvers. Next, we present an online basic feedback controller that integrates the feedforward control for the FWR’s flip control. Experimental results demonstrate the successful execution of the flip maneuvers without any mechanical modifications, highlighting the effectiveness of the proposed control strategy.