It is well known that in practical situations observe input - output data of an identified plant by ordinary least squares estimation method are biased.
In order to obtain consistent estimates a new type of modified least squares(MLS) estimation met...
It is well known that in practical situations observe input - output data of an identified plant by ordinary least squares estimation method are biased.
In order to obtain consistent estimates a new type of modified least squares(MLS) estimation method is presented in this paper. A designed first-order prefilter is connected parallelly to the input of the identified system. On the basis of asymptotic analysis, the noise variances can be estimated correctly by using the processed samped data.
It is shown that the presented MLS method based on MLS by Feng et al gives consistent estimation without a priori knowleadge of the input and ouptput noises and can be determined the estimation biases. The simulation results are presented to support the theoretical discussions.