Title :
Identification for Multivariate ARMA Systems without SPR Condition
Author_Institution :
Chinese Acad. of Sci., Beijing
Abstract :
When the ELS algorithm is applied to identifying the multivariate ARMA system A(z)yk = B(z)wk, the SPR condition is usually required and the covariance matrix Rw of Wk is normally not estimated. In this paper the recursive algorithms are proposed for estimating coefficients of A(z), B(z), and the covariance matrix Rw, of wk by recursively approximating the solution to the algebraic equation satisfied by the estimated parameters. The conditions imposed on the system are natural: stability of A(z), identifiability of the system, and iid for {wk}-The restrictive strictly positive realness condition (SPR) is not required and the algorithm is easily computable.
Keywords :
autoregressive moving average processes; covariance matrices; recursive estimation; algebraic equation; covariance matrix; multivariate ARMA systems identification; recursive algorithms; Control systems; Covariance matrix; Equations; Laboratories; Parameter estimation; Polynomials; Programmable control; Recursive estimation; Stability; Time series analysis; ARMA; adaptive spectral factorization; recursive identification; stochastic approximation; strong consistency;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4346938