Asymptotic properties of regression models of controlled plants

The paper is concerned with regression plant models restored by the method of least squares using a finite but sufficient number of experimental observations. Asymptotic properties of the correlation matrix of errors in estimates of unknown model parameters the r.m.s. error of the restored model used for conditional forecast of the plant output are studied. A method improving convergence of unknown parameter estimates is proposed.