State-space aerodynamic model reveals high force control authority and predictability in flapping flight.

Area of Science:

• Robotics
• Aerodynamics
• Biomechanics

Background:

• Flapping-wing flight in nature involves complex, high-degree-of-freedom wing motions.
• Modeling these unsteady, three-dimensional flows for accurate aerodynamic force prediction is computationally expensive and challenging.
• Existing models often lack the accuracy and generality needed for advanced robotic fliers.

Purpose of the Study:

• To develop a computationally efficient, data-driven state-space model for mapping wing kinematics to aerodynamic forces/moments.
• To surpass the accuracy and generality of current quasi-steady aerodynamic models for flapping flight.
• To assess the control authority of wing kinematic variables in generating aerodynamic forces.

Main Methods:

• Developed a 12-state data-driven state-space model trained on 548 flapping-wing motions.
• The model dynamically maps wing kinematics to aerodynamic forces/moments without explicit fluid flow data.
• Assessed the predictive power of wing motion history and the influence of kinematic variables like angle of attack.

Main Results:

• The developed model accurately predicts aerodynamic forces and moments, outperforming existing quasi-steady models.
• The model captures unsteady and nonlinear fluid effects using internal states, without direct fluid flow information.
• Wing motion history within a half-stroke cycle significantly predicts instantaneous forces/moments.
• Angle of attack, normal acceleration, and pitching motion were identified as key drivers of force generation.

Conclusions:

• Flapping flight possesses inherent high force control authority and predictability.
• The developed model offers a computationally efficient method for understanding and predicting flapping-wing aerodynamics.
• This research provides a foundation for designing more agile and stable bio-inspired aerial robotic fliers.