Choice of coefficient of criterion of a minimum of the resulting root-mean-square error for linear automatic control systems

The various approaches to the choice of a weight coefficient criterion for the resulting minimum root-mean-square error of linear automatic control systems are considered. This criterion allows us to define optimized meanings of system small parameters, minimizing the resulting error of the system, which is the summed dispersion of measurement noise and reproduction error of the determined or casual reference input. Changing the weight coefficient of the criterion, we give greater "weight" to that error, which strongly needs to be reduced.