Modeling multi-loop intelligent pilot control behavior for aircraft-pilot couplings analysis

Aircraft-pilot couplings (APCs) are one of the key factors that affect the flight safety of the modern aircraft. Among the several types of APCs, the nonlinear pilot induced oscillations caused by aircraft flight control system anomalies are extremely severe. In this paper, a multi-loop intelligent pilot model is presented for the analysis of the nonlinear pilot induced oscillations investigations. The multi-loop control tasks are introduced to define a typical multi-loop pilot modeling problem. The model is capable of describing the pilot's behavior during a multi-loop control task and analyzing the nonlinear pilot-induced oscillations when the flight control system is changed in different forms. Fuzzy control logic is designed to reflect the human pilot's behavior of making judgments. To be specific, the human pilot can change his/her control behavior adaptively when the aircraft flight control system falls into anomalies. Six cases of the abnormal flight control system are considered, and the control effects of the human pilot model are analyzed. The experimental results demonstrate that the human pilot can adjust the control strategy in different cases, which reflects the human pilot's adaptation to the changes of aircraft dynamics characteristics. Furthermore, it indicates that the human pilot model can obtain good control performance in tracking the command signal and can complete the task well facing the failures of the control system. Besides, the validity of the human pilot model is assessed by the scalogram-based PIO metric. The proposed pilot model can be applied in evaluating the aircraft loss-of-control events in the form of adverse aircraft-pilot couplings.