Active parametrical identification of stochastic linear continuous-discrete systems based on the experiment design in the presence of abnormal observations

Abstract

The procedure of active parametrical identification of stochastic linear continuous-discrete systems including robust estimation of parameters and optimal design of input signals is offered. A general case of entering unknown parameters into the equations of state and observation, initial conditions and covariance matrices of system noise and measurements is considered. The efficiency of this procedure is demonstrated by the example of a direct current motor control system.