Abstract

Pilot-Induced Oscillations (PIOs) are potentially hazardous piloting phenomena in which a pilot's control-inputs and the aircraft control-responses have (for any of a number of possible reasons) become out of phase. During PIOs, aggressive over-controlling on the part of the pilot in order to overcome a perceived lack of control can lead to complete loss of aircraft control. This study shows data recorded from a Cognionics dry electrode system during actual flight exercises can be used on a second-to-second basis to classify whether a pilot was undergoing a PIO event or if a PIO was imminent. If such PIO predictions could be made with adequate accuracy and robustness in real-time, they could form the basis of systems aimed at detecting and/or mitigating PIOs.

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