Weighted Null-Space Fitting for Cascade Networks with Arbitrary Location of Sensors and Excitation Signals

(creator_code:org_t)

Institute of Electrical and Electronics Engineers (IEEE), 2018
2018
English.
In: 57th IEEE Conference on Decision and Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538613955 ; , s. 4707-4712

Related links:: https://kth.diva-por... (primary) (Raw object); show more...; https://urn.kb.se/re...; https://doi.org/10.1...; show less...

Abstract Subject headings

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.

By the author/editor: Ferizbegovic, Mi ...; Galrinho, Miguel; Hjalmarsson, Håk ...

About the subject

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.