Vector ARMA Estimation: An Enhanced Subspace Approach
1999 (English)In: Proceedings of the 38th IEEE Conference on Decision and Control, 1999, 3665-3670 vol.4 p.Conference paper (Refereed)
A parameter estimation method for finite-dimensional multivariate linear stochastic systems is presented which is guaranteed to produce valid models close enough to the true underlying model, in a computational time of at most a polynomial order of the system dimension. This is achieved by combining the main features of certain stochastic subspace identification techniques together with sound statistical order estimation methods, matrix Schur restabilization procedures and multivariate covariance fitting, the latter formulated as linear matrix inequality problems. In this paper we make emphasis on the last issues mentioned, and provide an example of the overall performance for a multivariable case.
Place, publisher, year, edition, pages
1999. 3665-3670 vol.4 p.
Vector ARMA estimation, Semidefinite programming, Spectral estimation
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-91125DOI: 10.1109/CDC.1999.827923ISBN: 0-7803-5250-5OAI: oai:DiVA.org:liu-91125DiVA: diva2:618446
38th IEEE Conference on Decision and Control, Phoenix, AZ, USA, December, 1999