An Investigation of Sampled Data Models of the Human Operator in a Control System

An analytical and experimental study of a new class of human operator models, based on discrete rather than continuous operations is presented. A systematic study of the implications of intermittency by means of the theory of sampled-data control systems is described. The resulting models are consistent with the large body of experimental evidence concerning tracking. For the inputs considered, the outputs from the sampled-data models have certain characteristics which approximate experimental data more closely over a wider range of frequencies than those obtained from the quasilinear continuous models. Systematic procedures for construction of the proposed sampled-data model are presented, beginning with the measurement of power spectra and cross-spectra of the system. A preliminary analysis of transient response and stability of sampled data systems with variable sampling rates is presented as an introduction to the study of adaptive sampled data models.