Abstract: Current unsteady aerodynamic modeling methods at high angle of attack usually use stable vibration test data at multiple frequencies to predict stable hysteresis loop. However, the rapid maneuvering process of aircraft, such as post-stall maneuver, cannot be a constant and stable vibration, but an unstable dynamic process. Therefore, the aerodynamics would not reach a stable hysteresis loop, but would always be in the initial unstable process of entering the hysteresis loop. The vibration theory analysis shows that the dynamic response process of unstable aerodynamics has the unstable and stable stages. The traditional modeling method focuses on the stable stage, while the actual maneuvering process of aircraft is in the unstable stage. Based on the Least Squares Support Vector Machine (LS-SVM), an excitation input suitable for nonlinear system identification is introduced to model unsteady aerodynamic forces of any motion in the amplitude and frequency ranges at high angle of attack. After completing the model training, the method is applied to predict the lift coefficient, drag coefficient, and pitching moment coefficient of a wing at high angle of attack with different reference states in pitching motion. The results show that not only the stable hysteresis loop is accurately predicted, but also the initial unstable process of entering the hysteresis loop is accurately predicted. In addition, the results also show that the reference state has significant influence on the characteristics of aerodynamics in the initial process. Further validation also shows that modeling based on the stable hysteresis loop data can only predict the stable hysteresis loop, and cannot predict the unstable process of entering the hysteresis loop.

Key words: unsteady aerodynamics, high angle of attack, unstable dynamic process, least squares support vector machine, nonlinear system, system identification, input design