Statistical Identification of a Human-Operator Model in Control Systems Subject to Random Disturbances,
FOREIGN TECHNOLOGY DIV WRIGHT-PATTERSON AFB OH
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In investigating human-operator factors in manual-control systems subject to random disturbance effects, one can accept the hypothesis of a quasi-linear model assuming linearity and stationariness. For this purpose, one should identify the parameters of such a model, assuming that the operator acts, basically, as a linear member with a transmittance Hjw to a linear object Gjw, with the forcing action ut a stationary and ergodic random process. In order to find the optimum operator performance in terms of a rms linear approximation of Hjw, one has to minimize the functional J E ct - ct squared, with ct the real reaction measured at the operators output and ct the desired model reaction. Solution of the problem is best found in the frequencies region. A study was made of several different control situations which occur most frequently. Two specially-trained operators were tested under varying operating conditions. It was found that the adopted method proved well-chosen in all cases where hypothesis of a quasi-linear model for the statistical identification of dynamic human-operator factors is acceptable, and the action of the operator involved may be compared with the action of a classical continuous regulator.
- Human Factors Engineering and Man Machine Systems