Modeling Human Open-loop Tracking Behavior

A nonlinear generalization of the Adaptive Model Theory, nAMT, is compared with human open-loop tracking data across the same range of conditions. The resulting simulations produced effects that mirrored the closedand open-loop characteristics of the experimental response trajectories. This supports the use of an internal feedback loop for the inversion of external systems in the nAMT model. Other control-systems models (both AMT and feedback-error learning) were unable to reproduce the observed disparity between closedand open-loop results without fundamental modification. A low internal feedback loop-gain, incorporating a substantial derivative component, caused this effect. This low gain produced acceptable performance due to the relatively low target bandwidth used in the study, allowing the feedback control component to function. Maintenance of the loop-gain at the lowest possible levels is thought to maximize the internal stability of the inverse. The simulation work confirmed that the nAMT model is capable of reproducing human behavior under a wide range of conditions. Keywords—Internal models, motor learning, adaptive inverse control, motor control modelling, tracking task