Recursive identification of parameters in the minimum variance control

Abstract

This paper focus on the parameter recursive identification problems in minimum variance control system from the perspective of identification. Consider the unknown parameter vector of the ARMAX model in the minimum variance closed loop control, we propose multi-innovation recursive least-squares identification method and separable iterative recursive least-squares identification method to identify and estimate the unknown parameters vector in the ARMAX model on line. When excited by the white noise, the two identification methods will give the unbiased estimation about the unknown parameter vector. When excited by the color noise, only the separable iterative recursive least-squares identification method can give the unbiased estimation.