Automatica, Vol.35, No.7, 1243-1254, 1999
Consistency and asymptotic normality of some subspace algorithms for systems without observed inputs
Linear systems with unobserved white noise inputs are considered. A class of subspace estimates for the system matrices obtained by estimating the state in the first step is analyzed. The main result presented here states asymptotic normality of subspace estimates. In addition, a consistency result for the system matrix estimates is given. An algorithm to compute the asymptotic variances of the estimates is presented. In a final section the implications of the result are discussed.
Keywords:STOCHASTIC-PROCESSES;IDENTIFICATION