  This paper proposes an adaptive human pilot model that is able to mimic the
crossover model in the presence of uncertainties. The proposed structure is
based on the model reference adaptive control, and the adaptive laws are
obtained using the Lyapunov-Krasovskii stability criteria. The model can be
employed for human-in-the-loop stability and performance analyses incorporating
different types of controllers and plant types. For validation purposes, an
experimental setup is employed to collect data and a statistical analysis is
conducted to measure the predictive power of the pilot model.
