Multi-loop pilot behaviour identification in response to simultaneous visual and haptic stimuli

The goal of this paper is to better understand how the neuromuscular system of a pilot, or more generally an operator, adapts itself to different types of haptic aids during a pitch control task. A multi-loop pilot model, capable of describing the human behaviour during a tracking task, is presented. Three different identification techniques were investigated in order to simultaneously identify neuromuscular admittance and the visual response of a human pilot. In one of them, the various frequency response functions that build up the pilot model are identified using multi-inputs linear time-invariant models in ARX form. A second method makes use of cross-spectral densities and diagram block algebra to obtain the desired frequency response estimates. The identification techniques were validated using Monte Carlo simulations of a closed-loop control task. Both techniques were compared with the results of another identification method well known in literature and based on cross-spectral density estimates. All those methods were applied in an experimental setup in which pilots performed a pitch control task with different haptic aids. Two different haptic aids for tracking task are presented, a Direct Haptic Aid and an Indirect Haptic Aid. The two haptic aids were compared with a baseline condition in which no haptic force was used. The data obtained with the proposed method provide insight in how the pilot adapts his control behavior in relation to different haptic feedback schemes. From the experimental results it can be concluded that humans adapt their neuromuscular admittance in relation with different haptic aids. Furthermore, the two new identification techniques seemed to give more reliable admittance estimates.