Identification of human skill based on feedforward / feedback switched dynamical model

To realize the harmonious cooperation with the operator, the man-machine cooperative system must be designed so as to accommodate with the characteristics of the operator´s skill. One of the important considerations in the skill analysis is to investigate the switching mechanism underlying the skill dynamics. On the other hand, the combination of the feedforward and feedback schemes has been proved to work successfully in the modeling of human skill. In this paper, a new stochastic switched skill model for the sliding task, wherein a minimum jerk motion and feedback schemes are embedded in the different discrete states, is proposed. Then, the parameter estimation algorithm for the proposed switched skill model is derived. Finally, some advantages and applications of the proposed model are discussed.