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Weighted Null-Space Fitting for Cascade Networks with Arbitrary Location of Sensors and Excitation Signals
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-9368-3079
2018 (English)In: : 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 4707-4712Conference paper, Published paper (Refereed)
Abstract [en]

Identification of a complete dynamic network affected by sensor noise using the prediction error method is often too complex. One of the reasons for this complexity is the requirement to minimize a non-convex cost function, which becomes more difficult with more complex networks. In this paper, we consider serial cascade networks affected by sensor noise. Recently, the Weighted Null-Space Fitting method has been shown to be appropriate for this setting, providing asymptotically efficient estimates without suffering from non-convexity; however, applicability of the method was subject to some conditions on the locations of sensors and excitation signals. In this paper, we drop such conditions, proposing an extension of the method that is applicable to general serial cascade networks. We formulate an algorithm that describes application of the method in a general setting, and perform a simulation study to illustrate the performance of the method, which suggests that this extension is still asymptotically efficient.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 4707-4712
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-245000DOI: 10.1109/CDC.2018.8619410ISI: 000458114804056Scopus ID: 2-s2.0-85062173448ISBN: 978-1-5386-1395-5 (print)OAI: oai:DiVA.org:kth-245000DiVA, id: diva2:1293717
Conference
57th IEEE Conference on Decision and Control, CDC 2018; Centre of the Fontainebleau in Miami Beach, Miami; United States; 17 December 2018 through 19 December 2018;
Note

QC 20190305

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

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Ferizbegovic, MinaGalrinho, MiguelHjalmarsson, Håkan

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