Estimation of Large-Scale Implicit Models Using 2-Stage Methods

• Main Author: Rolf Henriksen
• Format: Article
• Language: English
• Published: Norwegian Society of Automatic Control 1985-01-01
• Series: Modeling, Identification and Control
• Subjects: Parameter estimation; large scale systems; two-stage methods; decentralized filtering; prediction error methods
• Online Access: http://www.mic-journal.no/PDF/1985/MIC-1985-1-1.pdf

The problem of estimating large scale implicit (non-recursive) models by two- stage methods is considered. The first stage of the methods is used to construct or estimate an explicit form of the total model, by constructing a minimal stochastic realization of the system. This model is then subsequently used in the second stage to generate instrumental variables for the purpose of estimating each sub-model separately. This latter stage can be carried out by utilizing a generalized least squares method, but most emphasis is put on utilizing decentralized filtering algorithms and a prediction error formulation. A note about the connection between the original TSLS-method (two-stage least squares method) and stochastic realization is also made.