On statistical optimization of interactive system components

The paper is concerned with statistical optimization of interactive system component whereby optimal gains of the actuator and indicator units are found as a function of human operator's characteristics and of the system noise level. The operator is assumed to act like a Kalman filter and be capable od adjusting (adapting) his parameters to those of the plant in compliance with his own functional of the performance criterion: this represents the operator's motivation for accuracy in stabilizing the plant parameters, intensity of “his own” control signal, and total power consumption of the system for control. Unlike conventional models, this model of human operator allows for possible adjustment of the neuromuscular system time constant. The analytical solution is investigated and experimentally tested for the problem of statistically optimal interaction of human operator with a dynamic first order process.