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

Authors: Rolf Henriksen,
Affiliation: NTNU, Department of Engineering Cybernetics
Reference: 1985, Vol 6, No 1, pp. 3-19.

Keywords: Parameter estimation, large scale systems, two-stage methods, decentralized filtering, prediction error methods, implicit models

Abstract: 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.

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  title={{Estimation of Large-Scale Implicit Models Using 2-Stage Methods}},
  author={Henriksen, Rolf},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}