Identification of dynamic models in complex networks with predictor error methods: predictor input selection

A.G. Dankers, P.M.J. Hof, Van den, X. Bombois, P.S.C. Heuberger

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53 Citaten (Scopus)
274 Downloads (Pure)

Samenvatting

This paper addresses the problem of obtaining an estimate of a particular module of interest that is embedded in a dynamic network with known interconnection structure. In this paper it is shown that there is considerable freedom as to which variables can be included as inputs to the predictor, while still obtaining consistent estimates of the particular module of interest. This freedom is encoded into sufficient conditions on the set of predictor inputs that allow for consistent identification of the module. The conditions can be used to design a sensor placement scheme, or to determine whether it is possible to obtain consistent estimates while refraining from measuring particular variables in the network. As identification methods the Direct and Two Stage Prediction-Error methods are considered. Algorithms are presented for checking the conditions using tools from graph theory.
Originele taal-2Engels
Pagina's (van-tot)937-952
Aantal pagina's16
TijdschriftIEEE Transactions on Automatic Control
Volume61
Nummer van het tijdschrift4
DOI's
StatusGepubliceerd - 25 mrt 2016

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