Method of predicting nonlinear pilot-induced oscillations due to flight control degradation based on digital virtual flight

Because few methods of predicting nonlinear pilot-induced oscillations are available, it is difficult to analyze the sensitive characteristics of such oscillations in the stage of aircraft scheme design. The pilot has the ability to self-adapt, and the control behavior may change before and after flight control degradation. To identify flight control degradation faults and adaptively adjust a pilot's manipulation behavior, three new modules, including pilot perception, flight control degradation judgment and adaptive adjustment, are established to construct a time-varying pilot model. Combined with a digital flight task model, a digital virtual flight simulation model of flight control degradation is built. An identification algorithm based on fuzzy logic is adopted to quantitatively evaluate the pilot-induced oscillation characteristics according to the numerical simulation results. Then, a nonlinear pilot-induced oscillation prediction method based on digital virtual flight is established. A pitch attitude tracking task is selected to predict the longitudinal, nonlinear pilot-induced oscillations. The results show that the prediction results of the simulations are basically consistent with those of a human-in-the-loop flight test with a ground simulator, which verifies the correctness of the proposed method. Through a sensitivity study of the stick force gradient after degradation, the influence of this parameter and the recommended value are determined. This method can be used to predict the nonlinear pilot-induced oscillation characteristics of fly-by-wire aircraft in the conceptual design stage and provide a theoretical reference for the optimal design of flight control systems.