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Weighted Null-Space Fitting for Identification of Cascade Networks⁎
KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0002-9368-3079
2018 (English)In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 856-861Article in journal (Refereed) Published
Abstract [en]

For identification of systems embedded in dynamic networks, the prediction error method (PEM) with a correct parametrization of the complete network provides asymptotically efficient estimates. However, the network complexity often hinders a successful application of PEM, which requires minimizing a non-convex cost function that can become more intricate for more complex networks. For this reason, identification in dynamic networks often focuses in obtaining consistent estimates of modules of interest. A downside of these approaches is that splitting the network in several modules for identification often costs asymptotic efficiency. In this paper, we consider dynamic networks with the modules connected in serial cascade, with measurements affected by sensor noise. We propose an algorithm that estimates all the modules in the network simultaneously without requiring the minimization of a non-convex cost function. This algorithm is an extension of Weighted Null-Space Fitting (WNSF), a weighted least-squares method that provides asymptotically efficient estimates for single-input single-output systems. We illustrate the performance of the algorithm with simulation studies, which suggest that a network WNSF method may also be asymptotically efficient when applied to cascade structures. Finally, we discuss the possibility of extension to more general networks affected by sensor noise.

Place, publisher, year, edition, pages
Elsevier B.V. , 2018. Vol. 51, no 15, p. 856-861
Keywords [en]
least-squares identification, networks, System identification, Cost benefit analysis, Cost functions, Embedded systems, Error analysis, Identification (control systems), Least squares approximations, Networks (circuits), Asymptotic efficiency, Asymptotically efficient, Identification of systems, Least squares identification, Nonconvex cost functions, Prediction error method, Single input single output systems, Weighted least squares, Complex networks
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-247497DOI: 10.1016/j.ifacol.2018.09.116ISI: 000446599200145Scopus ID: 2-s2.0-85054379687OAI: oai:DiVA.org:kth-247497DiVA, id: diva2:1301970
Note

QC20190403

Available from: 2019-04-03 Created: 2019-04-03 Last updated: 2019-05-22Bibliographically approved

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Galrinho, MiguelFerizbegovic, MinaHjalmarsson, Håkan

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