Modeling Human Multi-Channel Perception and Control Using Linear Time-Invariant Models

This paper introduces a two-step identification method of human multi-channel perception and control. In the first step, frequency response functions are identified using Linear Time-Invariant (LTI) models. The analytical predictions of bias and variance in the estimated frequency response functions are validated using Monte-Carlo simulations of a closed-loop control task and contrasted to a conventional method using Fourier Coefficients. For both methods, the analytical predictions are reliable, but the LTI method has lower bias and variance than Fourier Coefficients. It is further shown that the LTI method is more robust to higher levels of pilot remnant. Finally, both methods were successfully applied to experimental data from closed-loop control tasks with pilots